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Yun Chan 56a6e2da93 chore: 저장소 구조 정리 및 문서화, 첫 커밋 
- src/dist 산출물 분리 원칙 정리(.gitignore, .gitattributes)
- 루트 및 주요 폴더(config/scripts/prompts/tests/src, 런타임 폴더 5종)에
  안내용 README.md 추가
- CHANGELOG.md, LICENSE, docs/ops/05-release-and-versioning.md 추가
- docs/README.md 문서 지도 갱신
2026-09-04 09:25:44 +09:00

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# RAW RESEARCH DUMP — agent-a79a3a9066890f313
## ORIGINAL TASK PROMPT
오늘 날짜는 2026-09-02 이다. 너는 리서치 에이전트다. 반드시 먼저 ToolSearch 로 "select:WebSearch,WebFetch" 를 로드하고, WebSearch 로 최소 8회 이상 다양한 한국어/영어 질의를 던지고, 핵심 출처 페이지는 WebFetch 로 실제 열어 내용을 확인하라. 실제로 열어 확인한 항목만 verified_by_fetch=true 로 표시하라. 존재를 확인하지 못한 URL, GitHub 저장소, 논문, CLI 플래그는 절대 지어내지 말고 confidence='low' 로 표시하거나 제외하라. 한국 사이트(nedrug.mfds.go.kr, data.go.kr 등)는 WebFetch 가 실패할 수 있으니 실패하면 그 사실을 open_questions 에 적어라. 결과의 summary/detail/recommendations 는 한국어로 쓰되 고유명사·코드·플래그는 원문 유지. 코드 스니펫은 실제 동작 가능한 수준으로 구체적으로 작성하라. 최종 출력은 StructuredOutput 스키마에 맞춰라.
프로젝트 맥락: Windows 11 PC 에서 매일 06:00 에 한국 식약처 원료의약품 등록(DMF) 공고/현황을 크롤링하여 신규/변경/취하 건을 탐지하고, 탭(시트)별로 연동된 보기 좋은 xlsx 리포트를 생성한다. 크롤링·요약 일부를 AI 에이전트 CLI(Claude Code 의 'claude -p' headless 모드 등)로 non-interactive 하게 돌리고, 재부팅 후에도 자동 복구되는 서비스/스케줄러로 운영하며, 서비스가 죽으면 Windows 알림으로 복구 안내를 띄운다.
[축 3: 크롤링 방법론 이론 및 논문]
조사 항목 (논문은 반드시 저자·연도·게재처·URL(arXiv/ACM/IEEE/DBpia/RISS) 을 확인):
1) 웹 크롤러 아키텍처 고전: Mercator (Heydon & Najork 1999), Heritrix, 'Web Crawling' 서베이(Olston & Najork 2010) — 프론티어, politeness, 중복 제거, 재방문.
2) 증분 크롤링·변경 감지 이론: Cho & Garcia-Molina 'The Evolution of the Web and Implications for an Incremental Crawler'(2000), 'Effective Page Refresh Policies'(2003), 변경 빈도 추정(Poisson 모델), 이 프로젝트처럼 '하루 1회 공고 게시판 감시'에 적용하는 방법.
3) 구조적 데이터 추출: wrapper induction(Kushmerick 1997), RoadRunner(Crescenzi 2001), 테이블 추출, DOM 기반 XPath/CSS 셀렉터 안정성, 셀렉터 깨짐 탐지(schema drift) 기법.
4) LLM 기반 크롤링/추출 최신 논문(2023~2026): AutoScraper, WebVoyager, Mind2Web, 'LLM as wrapper generator' 류 — 결정론적 파서와 LLM 을 결합할 때의 권장 구조(LLM 은 셀렉터 생성/검증·요약만, 본 추출은 결정론적).
5) 중복·변경 탐지 알고리즘: SimHash/MinHash, 레코드 단위 diff(키 기반 upsert), 스냅샷 vs 이벤트 로그.
6) 크롤링 윤리·politeness 가이드(robots.txt RFC 9309, crawl-delay, 사용자 에이전트 식별).
7) 한국 학술 논문(DBpia/RISS/KCI)에서 '의약품 정보 크롤링', '공공 공고 모니터링 시스템' 관련 사례가 있으면 포함.
각 논문에 대해 이 프로젝트에 주는 실제 시사점을 2~3문장으로 적어라.
dimension 필드에는 "crawl-theory-papers" 를 넣어라.
## [SEARCH #1] Mercator scalable extensible web crawler Heydon Najork 1999
Web search results for query: "Mercator scalable extensible web crawler Heydon Najork 1999"
Links: [{"title":"[PDF] Mercator: A scalable, extensible Web crawler | Semantic Scholar","url":"https://www.semanticscholar.org/paper/Mercator:-A-scalable,-extensible-Web-crawler-Heydon-Najork/10e3137023969b3cf74b3488d5f5a29e7dd5bd80"},{"title":"Mercator: A scalable, extensible Web crawler | World Wide Web | Springer Nature Link","url":"https://link.springer.com/article/10.1023/A:1019213109274"},{"title":"Mercator: A Scalable, Extensible Web Crawler Allan Heydon and Marc Najork","url":"https://courses.cs.washington.edu/courses/cse454/15wi/papers/mercator.pdf"},{"title":"Mercator: A scalable, extensible Web crawler: World Wide Web: Vol 2, No 4","url":"https://dl.acm.org/doi/10.1023/A:1019213109274"},{"title":"Mercator: A Scalable, Extensible Web Crawler","url":"https://research.google/pubs/mercator-a-scalable-extensible-web-crawler/"},{"title":"(PDF) Mercator: A scalable, extensible Web crawler (1999) | Allan Heydon | 690 Citations","url":"https://scispace.com/papers/mercator-a-scalable-extensible-web-crawler-3pk6ponb3v"},{"title":"September 26, 2001 SRC Research Report 173 High-Performance Web Crawling","url":"https://www.cs.cornell.edu/courses/cs685/2002fa/mercator.pdf"},{"title":"Mercator: A Scalable, Extensible Web Crawler Allan Heydon and Marc Najork","url":"http://www.cs.ucr.edu/~vagelis/classes/CS242/publications/scalable-crawler.pdf"}]
Based on the search results, here's information about Mercator:
Mercator is a scalable, extensible web crawler written entirely in Java, developed by Allan Heydon and Marc Najork at Compaq Systems Research Center in Palo Alto, CA, with the paper published on June 26, 1999. The paper was published in World Wide Web journal, Volume 2, pages 219-229 in 1999.
The paper enumerates the major components of any scalable web crawler, comments on alternatives and tradeoffs in their design, and describes the particular components used in Mercator. It also describes Mercator's support for extensibility and customizability.
Mercator's performance was found to be comparable to that of other crawlers for which performance numbers have been published. Mercator is written entirely in Java and thus runs on any platform for which there exists a Java virtual machine, including Windows NT, Linux, Tru64 Unix, Solaris, and AIX.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #2] Olston Najork "Web Crawling" Foundations and Trends in Information Retrieval 2010
Web search results for query: "Olston Najork "Web Crawling" Foundations and Trends in Information Retrieval 2010"
Links: [{"title":"Web Crawling | Foundations and Trends in Information Retrieval | Emerald Publishing","url":"https://www.emerald.com/ftinr/article-abstract/4/3/175/1328663/Web-Crawling?redirectedFrom=PDF"},{"title":"Foundations and Trends R ⃝in Information Retrieval Vol. 4, No. 3 (2010) 175–246","url":"http://i.stanford.edu/~olston/publications/crawling_survey.pdf"},{"title":"Web Crawling (Foundations and Trends(r) in Information Retrieval) - Olston, Christopher; Najork, Marc: 9781601983220 - AbeBooks","url":"https://www.abebooks.com/9781601983220/Web-Crawling-Foundations-Trendsr-Information-1601983220/plp"},{"title":"Google Scholar","url":"https://scholar.google.com/scholar_lookup?title=Web+crawling&author=Olston%2C+C.&author=Najork%2C+M.&publication_year=2010&journal=Found.+Trends+Inf.+Retr.&volume=4&pages=175%E2%80%93246&doi=10.1561%2F1500000017"},{"title":"now publishers - Web Crawling","url":"https://www.nowpublishers.com/article/Details/INR-017"},{"title":"Web Crawling","url":"https://research.google/pubs/web-crawling/"},{"title":"(PDF) Web Crawling","url":"https://www.researchgate.net/publication/225844302_Web_Crawling"},{"title":"Amazon.com: Web Crawling (Foundations and Trends(r) in Information Retrieval): 9781601983220: Olston, Christopher, Najork, Marc: Books","url":"https://www.amazon.com/Crawling-Foundations-Trends-Information-Retrieval/dp/1601983220"},{"title":"A Brief History of Web Crawlers","url":"https://arxiv.org/pdf/1405.0749"},{"title":"iCrawl: Improving the Freshness of Web Collections by Integrating Social Web and Focused Web Crawling","url":"https://arxiv.org/pdf/1612.06202"}]
I found the publication you're looking for. Olston and Najork published "Web Crawling" in Foundations and Trends in Information Retrieval in 2010.
The article appears in Volume 4, Issue 3, pages 175–246 of the journal. It's a survey of the science and practice of web crawling that addresses challenges ranging from systems concerns such as managing very large data structures to theoretical questions such as how often to revisit evolving content sources, outlining fundamental challenges and describing state-of-the-art models and solutions.
The article is available through multiple sources including Emerald Publishing, Now Publishers, and Stanford's repository, with the DOI: 10.1561/1500000017.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #3] Cho Garcia-Molina "Effective Page Refresh Policies for Web Crawlers" ACM TODS 2003 Poisson
Web search results for query: "Cho Garcia-Molina "Effective Page Refresh Policies for Web Crawlers" ACM TODS 2003 Poisson"
Links: [{"title":"Effective page refresh policies for Web crawlers | ACM Transactions on Database Systems","url":"https://dl.acm.org/doi/10.1145/958942.958945"},{"title":"Effective Page Refresh Policies for Web Crawlers JUNGHOO CHO","url":"https://dl.acm.org/doi/pdf/10.1145/958942.958945"},{"title":"A Scalable Crawling Algorithm Utilizing Noisy Change-Indicating Signals","url":"https://arxiv.org/html/2502.02430"},{"title":"[PDF] Effective page refresh policies for Web crawlers | Semantic Scholar","url":"https://www.semanticscholar.org/paper/Effective-page-refresh-policies-for-Web-crawlers-Cho-Garcia-Molina/07523653232201428925b335ee5efd67ec54765e"},{"title":"Effective Page Refresh Policies For Web Crawlers JUNGHOO CHO","url":"http://oak.cs.ucla.edu/~cho/papers/cho-tods03.pdf"},{"title":"(PDF) Effective Page Refresh Policies for Web Crawlers","url":"https://www.researchgate.net/publication/200111226_Effective_Page_Refresh_Policies_for_Web_Crawlers"},{"title":"KR101757822B1 - 웹 크롤링 모니터링 시스템 및 방법 - Google Patents","url":"https://patents.google.com/patent/KR101757822B1/ko"},{"title":"A Dynamic Page-Refresh Index Policy for Web Crawlers | Springer Nature Link","url":"https://link.springer.com/chapter/10.1007/978-3-319-08219-6_4"},{"title":"Towards a Quality-Oriented Real-Time Web Crawler | SpringerLink","url":"https://link.springer.com/chapter/10.1007/978-3-642-16515-3_10"},{"title":"Age of Information for Updates with Distortion: Constant and Age-Dependent Distortion Constraints","url":"https://arxiv.org/pdf/1912.13493"}]
Based on the search results, I found the paper you're looking for:
"Effective Page Refresh Policies for Web Crawlers" by Junghoo Cho and Hector Garcia-Molina was published in ACM Transactions on Database Systems, volume 28, issue 4 (December 2003), pages 390–426.
The paper's key contribution is that a Poisson process is a good model to describe the changes of Web pages and the proposed refresh policies improve the "freshness" of data very significantly.
Regarding the Poisson model specifically, the time between changes follow an exponential distribution λe−λt if the change frequency of the page is λ. The paper validates this model through empirical analysis of actual web page changes.
The paper is available through the ACM Digital Library (https://dl.acm.org/doi/10.1145/958942.958945).
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #4] Cho Garcia-Molina "The Evolution of the Web and Implications for an Incremental Crawler" VLDB 2000
Web search results for query: "Cho Garcia-Molina "The Evolution of the Web and Implications for an Incremental Crawler" VLDB 2000"
Links: [{"title":"(PDF) Clustering-based incremental web crawling","url":"https://www.academia.edu/115717545/Clustering_based_incremental_web_crawling"},{"title":"Dealing with web data: history and look ahead: Proceedings of the VLDB Endowment: Vol 3, No 1-2","url":"https://dl.acm.org/doi/10.14778/1920841.1920846"},{"title":"A Framework for Incremental Domain-Specific Hidden Web Crawler | SpringerLink","url":"https://link.springer.com/chapter/10.1007/978-3-642-14834-7_39"},{"title":"Clustering-based incremental web crawling | ACM Transactions on Information Systems","url":"https://dl.acm.org/doi/10.1145/1852102.1852103"},{"title":"Topical web crawlers: Evaluating adaptive algorithms: ACM Transactions on Internet Technology: Vol 4, No 4","url":"https://dl.acm.org/doi/10.1145/1031114.1031117"},{"title":"A Framework for Incremental Deep Web Crawler Based on URL Classification | SpringerLink","url":"https://link.springer.com/content/pdf/10.1007/978-3-642-23982-3_37.pdf"},{"title":"Multiple-Goal Heuristic Search","url":"https://arxiv.org/pdf/1109.6618"},{"title":"Management Of Volatile Information In Incremental Web Crawler","url":"https://arxiv.org/pdf/0910.1869"},{"title":"The Evolution of the Web and Implications for an Incremental Crawler | Proceedings of the 26th International Conference on Very Large Data Bases","url":"https://dl.acm.org/doi/10.5555/645926.671679"},{"title":"[PDF] The Evolution of the Web and Implications for an Incremental Crawler | Semantic Scholar","url":"https://www.semanticscholar.org/paper/The-Evolution-of-the-Web-and-Implications-for-an-Cho-Garcia-Molina/ed7087560de484b922e316874a9076376a2a0186"}]
Based on the search results, I found information about the paper "The Evolution of the Web and Implications for an Incremental Crawler" by Cho and Garcia-Molina from VLDB 2000.
## Publication Details
The paper was authored by J. Cho and H. Garcia-Molina, published in 2000 as "The evolution of the Web and implications for an incremental crawler" in the Proceedings of the 26th International Conference on Very Large Data Bases (VLDB), pages 200-209, published by Morgan Kaufmann Publishers Inc., San Francisco, CA, USA.
## Content and Significance
The paper addressed challenges posed by the Web's high rate of change and unprecedented scale by collecting and analyzing Web history data and describing the architecture and associated algorithms for an incremental Web crawler that can provide more up-to-date data to users in a timely manner.
The paper compared various design choices for an incremental crawler and discussed their trade-offs, proposing an architecture for the incremental crawler that combines the best design choices.
This paper has become a highly influential work in web crawling research, as evidenced by its frequent citations in subsequent research on incremental web crawling and related topics.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #5] Kushmerick wrapper induction 1997 RoadRunner Crescenzi Mecca Merialdo 2001 VLDB
Web search results for query: "Kushmerick wrapper induction 1997 RoadRunner Crescenzi Mecca Merialdo 2001 VLDB"
Links: [{"title":"Wrapper maintenance: a machine learning approach: Journal of Artificial Intelligence Research: Vol 18, No 1","url":"https://dl.acm.org/doi/abs/10.5555/1622420.1622425"},{"title":"Populating the Semantic Web","url":"https://cdn.aaai.org/Workshops/2004/WS-04-01/WS04-01-006.pdf"},{"title":"Web page DOM node characterization and its application to page segmentation | Proceedings of the 3rd IEEE international conference on Internet multimedia services architecture and applications","url":"https://dl.acm.org/doi/10.5555/1812598.1812659"},{"title":"Structured Data Extraction: Wrapper Generation | Springer Nature Link","url":"https://link.springer.com/chapter/10.1007/978-3-642-19460-3_9"},{"title":"Automatic wrappers for large scale web extraction | Proceedings of the VLDB Endowment","url":"https://dx.doi.org/10.14778/1938545.1938547"},{"title":"Automatic Wrappers for Large Scale Web Extraction Nilesh Dalvi Yahoo! Research","url":"https://www.vldb.org/pvldb/vol4/p219-dalvi.pdf"},{"title":"EGA:An Algorithm for Automatic Semi-structured Web Documents Extraction | Springer Nature Link","url":"https://link.springer.com/chapter/10.1007/978-3-540-24571-1_69"},{"title":"Site-Wide Wrapper Induction for Life Science Deep Web Databases | SpringerLink","url":"http://link-springer-com-443.webvpn.fjmu.edu.cn/chapter/10.1007/978-3-642-02879-3_9"},{"title":"Wrapper Generation for Automatic Data Extraction from Large Web Sites | Springer Nature Link","url":"https://link.springer.com/chapter/10.1007/978-3-540-31970-2_3"}]
Based on the search results, here are the key findings related to your query:
**Kushmerick 1997 - Wrapper Induction:**
Kushmerick's "Wrapper induction for information extraction" was a PhD dissertation from 1997, with Daniel S. Weld as chairperson. Kushmerick, Weld, and Doorenbos published on wrapper induction for information extraction in Artificial Intelligence in 1997.
**RoadRunner 2001 - Crescenzi, Mecca, Merialdo:**
Crescenzi, Mecca, and Merialdo's "RoadRunner: Towards automatic data extraction from large web sites" was presented at the 27th Conference on Very Large Databases (VLDB) in Rome, Italy in 2001.
**Related Work:**
The WIEN system from Kushmerick and colleagues considers documents as a sequence of characters and defines various classes of wrapper languages, with the simplest being LR wrappers.
These works represent foundational research in wrapper induction technology for automated data extraction from web sources, with Kushmerick's 1997 dissertation pioneering the field and RoadRunner building on these concepts with automatic extraction capabilities for large websites.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #6] AutoScraper LLM web scraper generation EMNLP 2024 arXiv
Web search results for query: "AutoScraper LLM web scraper generation EMNLP 2024 arXiv"
Links: [{"title":"AutoScraper: A Progressive Understanding Web Agent for Web Scraper Generation - ADS","url":"https://ui.adsabs.harvard.edu/abs/2024arXiv240412753H/abstract"},{"title":"AutoScraper: A Progressive Understanding Web Agent for Web Scraper Generation - ACL Anthology","url":"https://aclanthology.org/2024.emnlp-main.141/"},{"title":"[PDF] AutoScraper: A Progressive Understanding Web Agent for Web Scraper Generation | Semantic Scholar","url":"https://www.semanticscholar.org/paper/AutoScraper:-A-Progressive-Understanding-Web-Agent-Huang-Gu/6c076122ea53e18180255bb96c9ad547bb88d283"},{"title":"[2404.12753] AutoScraper: A Progressive Understanding Web Agent for Web Scraper Generation","url":"https://arxiv.org/abs/2404.12753"},{"title":"Computation and Language Apr 2024","url":"https://arxiv.org/list/cs.CL/2024-04?skip=825&show=250"},{"title":"The AI Committee: A Multi-Agent Framework for Automated Validation and Remediation of Web-Sourced Data","url":"https://arxiv.org/pdf/2512.21481"},{"title":"Co-Scraper: query-aware DOM Pruning and Reusable Scraper Synthesis for Lightweight Web Data Extraction","url":"https://arxiv.org/pdf/2606.14821"},{"title":"AutoScraper: A Progressive Understanding Web Agent for Web Scraper Generation","url":"https://arxiv.org/pdf/2404.12753"}]
Based on the search results, I found detailed information about AutoScraper:
## AutoScraper: A Progressive Understanding Web Agent for Web Scraper Generation
AutoScraper was accepted to EMNLP 2024 and is available on arXiv as paper 2404.12753.
**Overview:**
The work introduces the paradigm of generating web scrapers with LLMs and proposes AutoScraper, a two-stage framework that can handle diverse and changing web environments more efficiently.
**Key Features:**
- AutoScraper leverages the hierarchical structure of HTML and similarity across different web pages for generating web scrapers.
- The authors propose a new executability metric for better measuring the performance of web scraper generation tasks.
- Comprehensive experiments with multiple LLMs demonstrate the effectiveness of the framework.
**Authors:**
The paper was authored by Wenhao Huang, Zhouhong Gu, Chenghao Peng, Jiaqing Liang, Zhixu Li, Yanghua Xiao, Liqian Wen, and Zulong Chen.
The work is open-source. You can access the paper on arXiv at https://arxiv.org/abs/2404.12753 and view it on the ACL Anthology at https://aclanthology.org/2024.emnlp-main.141/
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #7] Heritrix "An Introduction to Heritrix" Mohr Stack Kimpton Ranitovic 2004 IWAW
Web search results for query: "Heritrix "An Introduction to Heritrix" Mohr Stack Kimpton Ranitovic 2004 IWAW"
Links: [{"title":"Detecting Off-Topic Pages in Web Archives | SpringerLink","url":"https://link.springer.com/chapter/10.1007/978-3-319-24592-8_17"},{"title":"Web-Based Relation Extraction for the Food Domain | Springer Nature Link","url":"https://link.springer.com/chapter/10.1007/978-3-642-31178-9_25"},{"title":"The Wayback Machine: notes on a re-enchantment | Archival Science | Springer Nature Link","url":"https://link.springer.com/article/10.1007/s10502-020-09345-w"},{"title":"Users of Heritrix","url":"https://github.com/internetarchive/heritrix3/wiki/Users-of-Heritrix"},{"title":"Collecting Diachronic Affiliation Data for Faculty at HBCUs Using Memento - Zarrillo - 2022 - Proceedings of the Association for Information Science and Technology - Wiley Online Library","url":"https://asistdl.onlinelibrary.wiley.com/doi/10.1002/pra2.664"},{"title":"Exploring a Big Data Approach to Building a List Frame for Urban Agriculture: A Pilot Study in the City of Baltimore - Linda J. Young, Michael Hyman, Barbara R. Rater, 2018","url":"https://journals.sagepub.com/doi/10.2478/jos-2018-0015?icid=int.sj-abstract.citing-articles.26"},{"title":"A Framework for Evaluation of Composite Memento Temporal Coherence","url":"https://arxiv.org/pdf/1402.0928"},{"title":"Heritrix User Manual Internet Archive Kristinn Sigur#sson Michael Stack","url":"http://crawler.archive.org/articles/user_manual.pdf"},{"title":"Adapting the Hypercube Model to Archive Deferred Representations and Their Descendants","url":"https://arxiv.org/pdf/1601.05142"},{"title":"An Introduction To Heritrix Gordon Mohr Chief Technologist, Web Projects","url":"https://docs.huihoo.com/heritrix/An-Introduction-To-Heritrix.ppt"}]
I've found several search results related to your query. The paper "An Introduction to Heritrix: an open source archival quality web crawler" was authored by Mohr, Stack, Ranitovic, Avery, and Kimpton and presented in the Proceedings of the 4th international web archiving workshop IWAW'04 in July 2004 in Bath, UK.
The paper appeared on pages 109-115 of the workshop proceedings. Heritrix is the Internet Archive's open-source, extensible, web-scale, archival-quality web crawler project.
The paper is widely cited in academic literature related to web archiving and has been referenced by numerous institutions and researchers working on web preservation and archiving projects.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #8] RFC 9309 Robots Exclusion Protocol crawl-delay user-agent
Web search results for query: "RFC 9309 Robots Exclusion Protocol crawl-delay user-agent"
Links: [{"title":"How Attackers Exploit robots.txt? | Baeldung on Computer Science","url":"https://www.baeldung.com/cs/robots-txt-risk-threat"},{"title":"RFC 9309: Robots Exclusion Protocol","url":"https://www.rfc-editor.org/rfc/rfc9309.html"},{"title":"Respecting Robots Exclusion Protocol or robots.txt at Scale | by Rashad Moarref | GumGum Tech Blog | Medium","url":"https://medium.com/gumgum-tech/respecting-robots-exclusion-protocol-or-robots-txt-at-scale-60ee57dc1295"},{"title":"RFC 9309: Robots Exclusion Protocol | RFC Editor","url":"https://www.rfc-editor.org/info/rfc9309/"},{"title":"RFC 9309: Robots.txt Is Now an Official IETF Internet Standard (Robots Exclusion Protocol)","url":"https://www.searchengineworld.com/rfc9309-robots-txt-quietly-became-an-official-internet-standard"},{"title":"RFC 9309 Robots Exclusion Protocol Abstract","url":"https://www.ietf.org/rfc/rfc9309.pdf"},{"title":"RFC 9309: Robots Exclusion Protocol | Guide books","url":"https://dl.acm.org/doi/10.17487/RFC9309"},{"title":"RFC 9309 — Robots Exclusion Protocol — status, mechanics & checks — AgentGrade","url":"https://agentgrade.com/standards/rfc-9309"}]
Based on the search results, here's what I found about RFC 9309, the Robots Exclusion Protocol, and the specific directives you asked about:
## RFC 9309 Overview
The robots.txt file is described in the internet standard RFC 9309, which provides a "Robots Exclusion Protocol" (REP). This document specifies and extends the "Robots Exclusion Protocol" method originally defined by Martijn Koster in 1994 for service owners to control how content served by their services may be accessed, if at all, by automatic clients known as crawlers.
## Crawl-Delay
An important finding regarding crawl-delay: RFC 9309 intentionally excluded crawl-delay because there was no consistent real-world behavior to standardize. Crawl-delay contains the expected minimum interval between sequential requests that the server allows, but despite its use in practice, it was not included in the official standard.
## User-Agent
Crawlers set their own name, which is called a product token. The product token MUST contain only uppercase and lowercase letters ("a-z" and "A-Z"), underscores ("_"), and hyphens ("-"). The product token SHOULD be a substring of the identification string that the crawler sends to the service. For example, in the case of HTTP, the product token SHOULD be a substring in the User-Agent header.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #9] 의약품 정보 크롤링 논문 DBpia 식약처 공고 모니터링 시스템
Web search results for query: "의약품 정보 크롤링 논문 DBpia 식약처 공고 모니터링 시스템"
Links: [{"title":"GitHub - chanhee-kang/DBpia_crawler: 국내 논문 서지정보 사이트 DBpia 크롤링 프로그램","url":"https://github.com/chanhee-kang/DBpia_crawler"},{"title":"환자 맞춤형 의약품 투약량 적정성 제공 시스템 - 김정훈 - 경희대학교 : 논문 - DBpia","url":"https://www.dbpia.co.kr/journal/detail?nodeId=T15064378"},{"title":"DBpia - 국내 논문, 학술지, 잡지까지 제공하는 학술 AI 플랫폼","url":"https://www.dbpia.co.kr/"},{"title":"의약품 안전관리를 위한 빅데이터의 활용 - 대한의사협회지 - 대한의사협회 : 논문 - DBpia","url":"https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE10887640"},{"title":"의약품 이력추적 관리 탐정 <RFID> - 전기의세계 - 대한전기학회 : 논문 - DBpia","url":"https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE02482264"}]
웹 검색 결과를 정리하면 다음과 같습니다:
## 검색 결과 요약
귀하의 검색어와 관련된 다음과 같은 자료들이 발견되었습니다:
1. **DBpia 크롤링 프로그램** - 국내 논문 서지정보 사이트 DBpia 내의 논문제목, 저자, 퍼블리셔, 저널명, 볼륨, 날짜, 초록의 내용을 가져올 수 있는 프로그램이 GitHub에 공개되어 있습니다.
2. **의약품 투약 적정성 시스템** - 웹페이지, 모바일 앱, 전자차트 시스템(EMR) 연계를 위한 API, 투약 내역이 담긴 약 봉투 또는 처방전 바코드를 통해 실제 의료전문가가 활용할 수 있도록 점검시스템을 구현하여 공공에 배포한 관련 논문이 DBpia에 존재합니다.
3. **식약처 관련 의약품 관리 연구** - 의약품 안전관리, 용량 점검, 이력추적 관리 등 식약처와 관련된 다양한 논문들이 DBpia에 수록되어 있습니다.
특히 의약품 정보 크롤링과 식약처 공고 모니터링 시스템에 대한 학술 자료를 찾으시려면 DBpia 플랫폼에서 직접 검색하시는 것을 권장합니다.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #10] Charikar SimHash near-duplicate detection Manku Jain Sarma 2007 WWW
Web search results for query: "Charikar SimHash near-duplicate detection Manku Jain Sarma 2007 WWW"
Links: [{"title":"Detection of near-duplicate documents","url":"https://d3s.mff.cuni.cz/legacy/~holub/sw/shash/"},{"title":"A Fusion of Algorithms in Near Duplicate Document Detection | Springer Nature Link","url":"https://link.springer.com/chapter/10.1007/978-3-642-28320-8_20"},{"title":"Detecting near-duplicates for web crawling | Request PDF","url":"https://www.researchgate.net/publication/221022983_Detecting_near-duplicates_for_web_crawling"},{"title":"Moses Charikar","url":"https://en.wikipedia.org/wiki/Moses_Charikar"},{"title":"Probabilistic near-duplicate detection using simhash | Proceedings of the 20th ACM international conference on Information and knowledge management","url":"https://dl.acm.org/doi/10.1145/2063576.2063737"},{"title":"(PDF) Detection Of Duplicate And Near-Duplicate Content For Web Crawlers","url":"https://www.researchgate.net/publication/326553400_Detection_of_Duplicate_and_Near-Duplicate_Content_for_Web_Crawlers"},{"title":"Detecting Near-Duplicates for Web Crawling Gurmeet Singh Manku Google Inc.","url":"https://research.google.com/pubs/archive/33026.pdf"},{"title":"[PDF] Detecting near-duplicates for web crawling | Semantic Scholar","url":"https://semanticscholar.org/paper/Detecting-near-duplicates-for-web-crawling-Manku-Jain/2ef82a2621f237dcdca546658a6a4ea1c69a5a41"},{"title":"GitHub - scrapinghub/python-simhash: An efficient simhash implementation for python · GitHub","url":"https://github.com/scrapinghub/python-simhash"},{"title":"Probabilistic Near-Duplicate Detection Using Simhash","url":"https://www.researchgate.net/publication/221615307_Probabilistic_Near-Duplicate_Detection_Using_Simhash"}]
The search results provide comprehensive information about this topic. Here's what I found:
## Overview
Manku, Jain, and Sarma published "Detecting Near-Duplicates for Web Crawling" in the Proceedings of the 16th International Conference on World Wide Web in 2007. This work built upon earlier research by Charikar.
## Charikar's SimHash
Charikar's original work, "Similarity Estimation Techniques from Rounding Algorithms," was published in the Proceedings of the 34th Annual Symposium on Theory of Computing in 2002. Manku et al. demonstrated that Charikar's simhash is practically useful for identifying near-duplicates in web documents belonging to a multi-billion page repository.
## Key Contributions
The Manku, Jain, and Sarma work presents an algorithmic technique for identifying existing f-bit fingerprints that differ from a given fingerprint in at most k bit-positions, for small k. SimHash is a fingerprint technique having the quality that fingerprints of near-duplicates vary in a minor number of bit positions.
## Practical Applications
This technique has been successfully applied to near-duplicate detection of web crawls (Manku et al., 2007; Sood and Loguinov, 2011) and short text messages (Pi et al., 2009).
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #11] WebVoyager He 2024 arXiv Mind2Web Deng 2023 NeurIPS generalist web agent
Web search results for query: "WebVoyager He 2024 arXiv Mind2Web Deng 2023 NeurIPS generalist web agent"
Links: [{"title":"arXiv:2504.01382v2 [cs.AI] 11 May 2025","url":"https://arxiv.org/pdf/2504.01382"},{"title":"GitHub - OSU-NLP-Group/Mind2Web: [NeurIPS'23 Spotlight] \"Mind2Web: Towards a Generalist Agent for the Web\" -- the first LLM-based web agent and benchmark for generalist web agents · GitHub","url":"https://github.com/OSU-NLP-Group/Mind2Web"},{"title":"Mind2Web: Towards a Generalist Agent for the Web","url":"https://papers.nips.cc/paper_files/paper/2023/hash/5950bf290a1570ea401bf98882128160-Abstract-Datasets_and_Benchmarks.html"},{"title":"OpenWebVoyager: Building Multimodal Web Agents via Iterative Real-World Exploration, Feedback and Optimization","url":"https://arxiv.org/pdf/2410.19609"},{"title":"Mind2Web: Towards a Generalist Agent for the Web | OpenReview","url":"https://openreview.net/forum?id=kiYqbO3wqw"},{"title":"NeurIPS Poster Mind2Web: Towards a Generalist Agent for the Web","url":"https://neurips.cc/virtual/2023/poster/73485"},{"title":"MIND2WEB: Towards a Generalist Agent for the Web Xiang Deng∗ Yu Gu Boyuan Zheng","url":"https://proceedings.neurips.cc/paper_files/paper/2023/file/5950bf290a1570ea401bf98882128160-Paper-Datasets_and_Benchmarks.pdf"},{"title":"Mind2Web: Towards a Generalist Agent for the Web","url":"https://osu-nlp-group.github.io/Mind2Web/"},{"title":"[PDF] Mind2Web: Towards a Generalist Agent for the Web | Semantic Scholar","url":"https://www.semanticscholar.org/paper/Mind2Web:-Towards-a-Generalist-Agent-for-the-Web-Deng-Gu/58f8925a8b87054ad0635a6398a7fe24935b1604"}]
Based on the search results, here's information about the papers and projects you mentioned:
## Mind2Web (Deng et al., 2023)
Mind2Web is the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. The dataset contains over 2,000 open-ended tasks collected from 137 websites spanning 31 domains and crowdsourced action sequences for the tasks.
Mind2Web provides three necessary ingredients for building generalist web agents: 1) diverse domains, websites, and tasks, 2) use of real-world websites instead of simulated and simplified ones, and 3) a broad spectrum of user interaction patterns. The paper was published at NeurIPS 2023 in the Datasets and Benchmarks track.
## WebVoyager (He et al., 2024)
WebVoyager by Hongliang He, Wenlin Yao, and colleagues was published in 2024 as an arXiv preprint (arXiv:2401.13919), building an end-to-end web agent with large multimodal models.
## Relationship Between the Two
The tasks in WebVoyager are synthesized by using modified tasks from Mind2Web as seeds and prompting a language model to generate additional ones. Mind2Web and WebArena represent the most widely used offline and sandboxed online environments for evaluation, while WebVoyager has gained attention due to its evaluation on online websites.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #12] web scraper selector breakage detection schema drift robust XPath wrapper maintenance paper
Web search results for query: "web scraper selector breakage detection schema drift robust XPath wrapper maintenance paper"
Links: [{"title":"How to Fix Web Scraping Errors: 2026 Complete Troubleshooting Guide","url":"https://www.promptcloud.com/blog/how-to-fix-web-scraping-errors-2026/"},{"title":"Web Scraping With XPath and CSS Selectors: which selector to reach for, and when","url":"https://crawlbase.com/blog/web-scraping-with-xpath-and-css-selectors/"},{"title":"When the Scraper Breaks Itself: Building a Self-Healing CSS Selector Repair System - DEV Community","url":"https://dev.to/viniciuspuerto/when-the-scraper-breaks-itself-building-a-self-healing-css-selector-repair-system-312d"},{"title":"Managing Change in Web Scraping: 10 Critical Challenges","url":"https://www.promptcloud.com/blog/managing-change-in-web-scraping-10-challenges/"},{"title":"What are CSS selectors and XPath in web extraction? | Firecrawl Glossary","url":"https://www.firecrawl.dev/glossary/web-extraction-apis/what-are-css-selectors-xpath-web-extraction"},{"title":"What is an xpath selector in web scraping? | Firecrawl Glossary","url":"https://www.firecrawl.dev/glossary/web-scraping-apis/what-is-xpath-selector-in-web-scraping"},{"title":"Robust wrappers for web extraction","url":"https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/8762829"}]
I found relevant results about web scraper selector breakage, schema drift detection, and XPath wrapper robustness. Here's what the search revealed:
## Key Findings
### Selector Breakage and Schema Drift
Schema drift occurs when page structure changes slightly, breaking CSS or XPath selectors. Production web scrapers depend on CSS selectors and XPath expressions authored against a snapshot of a website's DOM, and when sites redesign their layout, rename classes, or restructure tables, those selectors silently return nothing or return wrong data.
### Detection and Monitoring
Validation checks include running nightly validation comparing output field counts to historical norms, and implementing selector versioning by tagging scrapers with schema dates and auto-flagging anomalies. The challenge is that selectors often still match something—just not the right node, creating silent correctness drift.
### Robust XPath and CSS Practices
It's better to prefer stable attributes over visual classes, as data-testid, id, itemprop, or ARIA role are far more likely to outlive a restyle. Long, deep selector chains encode the entire layout, so any wrapper added along that path breaks the selector.
### Academic Work on Wrapper Maintenance
Path expressions are called wrappers, and while conventional wrapper use is effective for extraction, it suffers from a fundamental problem: underlying web pages frequently change, which may cause wrappers to break, requiring new wrappers to be learned to accommodate the changes.
The search results show this is an active area of research and practical concern in web scraping systems, with both detection strategies and robust design practices documented.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [FETCH #1] https://courses.cs.washington.edu/courses/cse454/15wi/papers/mercator.pdf
**ASK:** Summarize the architecture components: URL frontier, DNS resolver, content-seen test (fingerprints), URL-seen test, politeness (one host per queue), checkpointing, extensibility. Include authors, year, venue.
I appreciate your detailed instructions, but I need to point out that the web page content provided is a login/identity provider selection page for the University of Washington's Computer Science & Engineering department. It contains no information about:
- URL frontier architecture
- DNS resolver components
- Content-seen test (fingerprints)
- URL-seen test mechanisms
- Politeness policies (host-per-queue)
- Checkpointing systems
- Extensibility frameworks
- Academic authors or publication venues
This appears to be a mismatch between your question (which seems to ask about web crawler architecture components, possibly referencing the Mercator or similar crawling system papers) and the actual page content provided.
To properly answer your question about these architectural components, I would need access to the relevant academic paper or technical documentation describing a web crawling system. Could you provide the correct source material?
## [FETCH #2] https://research.google.com/pubs/archive/33026.pdf
**ASK:** Summarize authors, venue, year, the simhash technique, the 64-bit fingerprint, Hamming distance k=3 threshold, and the algorithm for finding fingerprints differing in k bits. Mention Charikar 2002 reference.
REDIRECT DETECTED: The URL redirects to a location that was not fetched automatically.
Original URL: https://research.google.com/pubs/archive/33026.pdf
Redirect URL (from the server's Location header — server-supplied, not verified): https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/33026.pdf
Status: 301 Moved Permanently
To complete your request, I need to fetch content from the redirected URL. Please use WebFetch again with these parameters:
- url: "https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/33026.pdf"
- prompt: "Summarize authors, venue, year, the simhash technique, the 64-bit fingerprint, Hamming distance k=3 threshold, and the algorithm for finding fingerprints differing in k bits. Mention Charikar 2002 reference."
## [FETCH #3] https://arxiv.org/abs/2404.12753
**ASK:** Summarize authors, venue, date, the two-stage framework (progressive generation and synthesis), executability metric, and main results. Is there a GitHub link?
# AutoScraper Paper Summary
**Authors:** Wenhao Huang, Zhouhong Gu, Chenghao Peng, Zhixu Li, Jiaqing Liang, Yanghua Xiao, Liqian Wen, and Zulong Chen
**Venue & Date:** EMNLP 2024; submitted April 19, 2024 (revised September 26, 2024)
**Two-Stage Framework:** AutoScraper employs a progressive generation and synthesis approach that "leverages the hierarchical structure of HTML and similarity across different web pages" to create web scrapers adaptable to diverse websites.
**Executability Metric:** The authors introduced a novel performance measurement specifically designed for assessing web scraper generation tasks, addressing limitations in existing evaluation methods.
**Main Results:** The research demonstrates that AutoScraper outperforms both wrapper-based methods (limited adaptability) and language agent approaches (poor reusability). Comprehensive experiments across multiple LLMs validate the framework's effectiveness in handling changing web environments.
**GitHub Link:** Yes—the paper references code availability at `https://github.com/EZ-hwh/AutoScraper`
## [FETCH #4] https://dl.acm.org/doi/10.5555/645926.671679
**ASK:** Give the abstract, authors, venue, pages, year and key findings about how often pages change, half-life of pages, and incremental vs periodic crawler design.
The server returned HTTP 403 Forbidden.
The response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.
## [FETCH #5] https://www.rfc-editor.org/rfc/rfc9309.html
**ASK:** Summarize: title, date, authors, key rules: user-agent product token, allow/disallow matching rules, caching of robots.txt (24 hours), handling of 4xx/5xx status, max file size 500 KiB, and whether crawl-delay is defined. Quote key sentences.
# RFC 9309: Robots Exclusion Protocol Summary
**Title:** Robots Exclusion Protocol (REP)
**Date:** September 2022
**Authors:** M. Koster, G. Illyes, H. Zeller, L. Sassman (Google LLC)
## Key Rules
**User-Agent Product Token:**
The specification requires that product tokens "MUST contain only uppercase and lowercase letters ('a-z' and 'A-Z'), underscores ('_'), and hyphens ('-')." Matching must be case-insensitive, and if multiple groups match, their rules combine into one.
**Allow/Disallow Matching:**
"The most specific match found MUST be used. The most specific match is the match that has the most octets." Path matching is case-sensitive and starts from the first character.
**Caching:**
"Crawlers SHOULD NOT use the cached version for more than 24 hours, unless the robots.txt file is unreachable."
**HTTP Status Handling:**
- **4xx errors:** "If a server status code indicates that the robots.txt file is unavailable to the crawler, then the crawler MAY access any resources."
- **5xx errors:** "If the robots.txt file is unreachable due to server or network errors, this means the robots.txt file is undefined and the crawler MUST assume complete disallow."
**File Size Limit:**
"The parsing limit MUST be at least 500 kibibytes [KiB]."
**Crawl-Delay:**
The specification does **not define crawl-delay**. This is notably absent from the protocol.
## [FETCH #6] https://arxiv.org/abs/2606.14821
**ASK:** Does this paper exist? If so give title, authors, date, abstract summary: query-aware DOM pruning and reusable scraper synthesis.
# Paper Confirmation
Yes, this paper exists.
**Title:** "Co-Scraper: query-aware DOM Pruning and Reusable Scraper Synthesis for Lightweight Web Data Extraction"
**Authors:** Shoupeng Wang, Jiantao Qiu, Wuyang Zhang, Conghui He
**Date:** Submitted June 12, 2026
**arXiv ID:** 2606.14821
**Abstract Summary:**
The research addresses automated web content extraction by developing a framework that generates reusable scrapers for similar pages. The two-stage approach combines DOM pruning informed by query parameters with extraction strategy induction. Using a fine-tuned language model, it transforms HTML into executable wrappers. The system demonstrated strong performance on benchmark tests, achieving an F1 score of 94.78% and reuse success rate of 90.39%, offering "a highly efficient approach for web data acquisition tasks."
## [FETCH #7] https://arxiv.org/abs/2401.13919
**ASK:** Summarize authors, date, venue (ACL 2024?), the multimodal web agent approach (screenshots + set-of-mark), task success rates, and limitations.
# WebVoyager: Web Agent Summary
**Authors & Venue:**
Led by Hongliang He and seven co-authors, the paper was accepted to ACL 2024 (main conference). First submitted January 25, 2024, with the final version released June 6, 2024.
**Multimodal Approach:**
WebVoyager leverages large multimodal models to process visual webpage screenshots alongside text. The system interacts with real-world websites end-to-end, moving beyond earlier agents confined to simulators or static snapshots.
**Performance Metrics:**
The agent achieved "a 59.1% task success rate on our benchmark, significantly surpassing the performance of both GPT-4 (All Tools) and the WebVoyager (text-only) setups." The evaluation protocol using GPT-4V achieved 85.3% agreement with human judgments.
**Benchmark:**
Researchers compiled real-world tasks from 15 popular websites and developed an automatic evaluation framework leveraging multimodal understanding capabilities.
**Limitations:**
The abstract doesn't explicitly detail limitations. However, the gap between WebVoyager's 59.1% success rate and perfect performance suggests challenges remain in complex web navigation and task completion in production environments.
**Availability:**
Code and data are released on GitHub.
## [FETCH #8] https://arxiv.org/abs/2512.21481
**ASK:** Does this paper exist? If so give title, authors, date, abstract summary about multi-agent validation and remediation of web-sourced data.
# Yes, this paper exists.
**Title:** The AI Committee: A Multi-Agent Framework for Automated Validation and Remediation of Web-Sourced Data
**Authors:** Sunith Vallabhaneni, Thomas Berkane, Maimuna Majumder
**Date:** Submitted December 25, 2025 (arXiv:2512.21481)
**Abstract Summary:**
The paper addresses the challenge of manually validating web-sourced research data by proposing a specialized multi-agent system. The framework tackles common LLM agent failures like "hallucinating or omitting values, misinterpreting page semantics, and failing to detect invalid information."
Each agent handles distinct quality assurance tasks including source verification and fact-checking. The system achieves "data completeness up to 78.7% and precision up to 100%" across three real-world datasets without requiring task-specific training. The authors released it as open-source software and demonstrated performance across different language models.
## [FETCH #9] https://papers.nips.cc/paper_files/paper/2023/hash/5950bf290a1570ea401bf98882128160-Abstract-Datasets_and_Benchmarks.html
**ASK:** Give title, authors, venue, abstract summary, dataset size, and the MindAct framework (small LM for candidate element ranking + LLM).
# Mind2Web: Research Paper Summary
**Title:** Mind2Web: Towards a Generalist Agent for the Web
**Authors:** Xiang Deng, Yu Gu, Boyuan Zheng, Shijie Chen, Sam Stevens, Boshi Wang, Huan Sun, Yu Su
**Venue:** Advances in Neural Information Processing Systems 36 (NeurIPS 2023), Datasets and Benchmarks Track
**Abstract Summary:**
This work introduces the first dataset designed for training generalist web agents capable of executing complex instructions across diverse websites. The researchers collected "over 2,000 open-ended tasks" from 137 websites spanning 31 domains with crowdsourced action sequences. The dataset addresses three critical needs: domain diversity, real-world websites, and varied interaction patterns. The team explores leveraging large language models for web agents while addressing scalability challenges.
**Dataset Size:** 2,000+ tasks across 137 websites in 31 domains
**Filtering Approach:**
The researchers' solution employs a two-stage methodology: "filtering it with a small LM significantly improves the effectiveness and efficiency of LLMs." This preprocessing step addresses the constraint that raw HTML from real websites exceeds LLM input capacity, enabling more effective agent performance on unseen domains.
## [FETCH #10] http://i.stanford.edu/~olston/publications/crawling_survey.pdf
**ASK:** Summarize the table of contents and key sections of this survey: crawler architecture (frontier, politeness, duplicate detection/URL seen test), incremental crawling and revisitation (freshness, age, change frequency estimation, Poisson model), and any recommendations. Give authors, year, venue, volume/pages.
connect ECONNREFUSED 171.64.75.45:443
## [FETCH #11] http://oak.cs.ucla.edu/~cho/papers/cho-tods03.pdf
**ASK:** Summarize: authors, venue, year, key contributions. Explain the freshness and age metrics, the Poisson change model, the finding about uniform vs proportional refresh policies, and how change frequency is estimated. Include any formulas.
connect ECONNREFUSED 131.179.64.202:443
## [SEARCH #13] Broder "On the resemblance and containment of documents" 1997 MinHash shingling
Web search results for query: "Broder "On the resemblance and containment of documents" 1997 MinHash shingling"
Links: [{"title":"On the Resemblance and Containment of Documents | BibSonomy","url":"https://www.bibsonomy.org/bibtex/278b3f3faced79adfcda4e3a57f7e57ff/schmitz"},{"title":"(PDF) On the Resemblance and Containment of Documents","url":"https://www.researchgate.net/publication/262333747_On_the_Resemblance_and_Containment_of_Documents"},{"title":"Set similarity search beyond MinHash | Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing","url":"https://dl.acm.org/doi/10.1145/3055399.3055443"},{"title":"C-MinHash: Practically Reducing Two Permutations to Just One","url":"https://arxiv.org/pdf/2109.04595"},{"title":"[PDF] On the resemblance and containment of documents | Semantic Scholar","url":"https://www.semanticscholar.org/paper/On-the-resemblance-and-containment-of-documents-Broder/8addb1718c2bc6bbb0d82cd1a57b41198bf65965"},{"title":"C-MinHash: Rigorously Reducing $K$ Permutations to Two","url":"https://arxiv.org/pdf/2109.03337"},{"title":"On the resemblance and containment of documents","url":"https://www.researchgate.net/profile/Andrei-Broder/publication/262333747_On_the_Resemblance_and_Containment_of_Documents/links/02e7e529d69d5de80a000000/On-the-Resemblance-and-Containment-of-Documents.pdf"},{"title":"b-Bit Minwise Hashing","url":"https://arxiv.org/pdf/0910.3349"},{"title":"Exact Weighted Minwise Hashing in Constant Time","url":"https://arxiv.org/pdf/1602.08393"},{"title":"HyperMinHash: MinHash in LogLog space","url":"https://arxiv.org/pdf/1710.08436"}]
I found several relevant sources for your search. Here's what I found:
Andrei Z. Broder's 1997 paper "On the resemblance and containment of documents" was published in Compression and Complexity of Sequences 1997 by IEEE, pages 21-29.
Broder introduced the MinHash sketching technique, which provides an efficient probabilistic approximation of the Jaccard similarity coefficient between two sets. The basic approach expresses resemblance and containment as set intersection problems evaluated by random sampling, with the number of common shingles in the sample having a hypergeometric distribution.
The probabilistic resemblance framework of Broder (1997) has been used in modern text deduplication pipelines, where text is shingled into word n-grams. The algorithm for filtering near-duplicate documents has been successfully implemented and used in the context of the AltaVista search engine.
The paper appears to be foundational work in similarity detection, with MinHash becoming a widely-used technique for computing set similarity in information retrieval and data deduplication applications.
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## [SEARCH #14] Dalvi Kumar Soliman "Robust web extraction" probabilistic tree-edit model SIGMOD 2009 XPath robustness
Web search results for query: "Dalvi Kumar Soliman "Robust web extraction" probabilistic tree-edit model SIGMOD 2009 XPath robustness"
Links: [{"title":"Web data extraction, applications and techniques | Knowledge-Based Systems","url":"https://dl.acm.org/doi/abs/10.1016/j.knosys.2014.07.007"},{"title":"Robust Web Data Extraction: A Novel Approach Based on Minimum Cost Script Edit Model | SpringerLink","url":"https://link.springer.com/chapter/10.1007/978-3-642-33469-6_62"},{"title":"Early Steps Toward Web‐Scale Information Extraction with LODIE | AI Magazine","url":"https://dl.acm.org/doi/10.1609/aimag.v36i1.2567"},{"title":"Chinese News Data Extraction System Based on Readability Algorithm | SpringerLink","url":"https://link.springer.com/chapter/10.1007/978-981-15-8083-3_14"},{"title":"Research on Adaptive Wrapper in Deep Web Data Extraction | Springer Nature Link","url":"https://link.springer.com/chapter/10.1007/978-3-319-27293-1_36"},{"title":"Robust web extraction: An approach based on a probabilistic tree-edit model | Request PDF","url":"https://www.researchgate.net/publication/221214620_Robust_web_extraction_An_approach_based_on_a_probabilistic_tree-edit_model"},{"title":"DIADEM: Domains to Databases | Springer Nature Link","url":"https://link.springer.com/chapter/10.1007/978-3-642-32600-4_1"},{"title":"Visual Template Inference for Data Extraction from Documents | Proceedings of the ACM on Management of Data","url":"https://dl.acm.org/doi/abs/10.1145/3769840"},{"title":"dblp: Nilesh N. Dalvi","url":"https://dblp2.uni-trier.de/pers/hd/d/Dalvi:Nilesh_N="},{"title":"Automatic Wrappers for Large Scale Web Extraction Nilesh Dalvi Yahoo! Research","url":"https://www.vldb.org/pvldb/vol4/p219-dalvi.pdf"}]
Based on the search results, I found information about the research you're looking for:
Dalvi, Kumar, and Soliman presented "Robust web extraction: an approach based on a probabilistic tree-edit model" at the ACM International Conference on Management of Data (SIGMOD 2009) in Providence, Rhode Island, USA.
Note that while the SIGMOD 2009 paper was authored by Dalvi, Bohannon, and Sha, Dalvi, Kumar, and Soliman collaborated on a related work titled "Automatic Wrappers for Large Scale Web Extraction" published in VLDB in 2011.
The research addressed how on script-generated websites, many documents share common HTML tree structure, allowing wrappers to effectively extract information, but as scripts and tree structures evolve over time, wrappers can break, resulting in high costs of maintaining them.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #15] KCI 논문 웹 크롤링 공고 게시판 변경 감지 모니터링 시스템 설계 구현
Web search results for query: "KCI 논문 웹 크롤링 공고 게시판 변경 감지 모니터링 시스템 설계 구현"
Links: [{"title":"웹 사이트 컨텐츠 변경 모니터링 시스템 - of DSpace - KCI","url":"https://dspace.kci.go.kr/handle/kci/355955"},{"title":"[논문]실시간 웹 크롤링 분산 모니터링 시스템 설계 및 구현","url":"https://scienceon.kisti.re.kr/srch/selectPORSrchArticle.do?cn=JAKO201909258120005"},{"title":"웹 사이트 컨텐츠 변경 모니터링 시스템","url":"https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART000881131"},{"title":"한국학술지인용색인(Korea Citation Index)","url":"https://www.kci.go.kr/kciportal/main.kci"},{"title":"[논문]동적인 URL 수집 정책을 이용한 분산 웹 크롤링 시스템","url":"https://scienceon.kisti.re.kr/srch/selectPORSrchArticle.do?cn=DIKO0014012605"},{"title":"KR101757822B1 - 웹 크롤링 모니터링 시스템 및 방법 - Google Patents","url":"https://patents.google.com/patent/KR101757822B1/ko"},{"title":"KCI 문헌 유사도 검사 서비스","url":"https://check.kci.go.kr/"},{"title":"KCI 국내 학술지 인용색인 정보 포털입니다.","url":"https://www.kci.go.kr/"},{"title":"KR101213930B1 - 결정 이론 웹 크롤링, 및 웹 페이지 변경의 예측 - Google Patents","url":"https://patents.google.com/patent/KR101213930B1/ko"},{"title":"실시간 웹 게시판 모니터링 및 모바일웹을 이용한 알람 서비스 개발","url":"https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART001648031"}]
검색 결과를 정리하면 다음과 같습니다:
## 검색 결과
웹 크롤링과 웹사이트 변경 감지 모니터링에 관련된 여러 논문들이 발견되었습니다:
**1. 웹 사이트 컨텐츠 변경 모니터링 시스템**
웹 사이트 문서의 변경을 모니터링하기 위하여 모니터링할 대상 URL, 모니터링 조건, 모니터링 주기 등을 사용자가 정의하면, 변경이 발생할 경우 사용자에게 알람이나 E-mail를 통하여 자동으로 통지하여 주는 웹 사이트 컨텐츠 변경 모니터링 시스템을 설계 및 구현한 논문이 있습니다.
**2. 실시간 웹 크롤링 분산 모니터링 시스템**
검색 엔진과 같은 여러 사이트에서는 데이터의 최신 상태 유지를 위해 웹 크롤링을 하며, 웹 크롤링은 대부분 방문한 사이트의 모든 페이지의 복사본을 생성하는 데 사용되고 검색 엔진은 이렇게 생성된 페이지를 더욱 빠른 검색을 위해 인덱싱합니다.
**3. 웹 게시판 모니터링 및 알람 서비스**
모니터링과 같은 실시간성이 필요한 서비스에 모바일웹을 이용하여 그 효과를 극대화하고, 모바일 웹은 언제 어디서나 접속할 수 있다는 장점으로 인하여 실시간적인 요소가 필요한 서비스에 적합합니다.
이러한 논문들은 KCI(한국학술지인용색인)와 KISTI 등의 국내 학술 데이터베이스에서 찾을 수 있습니다.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #16] RISS 학위논문 의약품 허가 정보 크롤링 자동 수집 시스템 식품의약품안전처 nedrug
Web search results for query: "RISS 학위논문 의약품 허가 정보 크롤링 자동 수집 시스템 식품의약품안전처 nedrug"
Links: [{"title":"https://nedrug.mfds.go.kr/index","url":"https://nedrug.mfds.go.kr/index"},{"title":"의약품안전나라 > 의약품등 검색 - 식품의약품안전처","url":"https://nedrug.mfds.go.kr/searchDrug"},{"title":"약품/식품정보 | 국가건강정보포털 | 질병관리청","url":"https://health.kdca.go.kr/healthinfo/biz/health/gnrlzHealthInfo/healthInfo/medcinFoodInfoMain.do"},{"title":"약학정보원 - 대한민국 의약품정보의 표준","url":"https://health.kr/"},{"title":"RISS(리스,학술연구정보서비스) - 국내·국외 학술정보를 제공하는 대국민 서비스","url":"https://www.riss.kr/index.do"},{"title":"https:/nedrug.mfds.go.kr - 식품의약품안전처","url":"https://nedrug.mfds.go.kr/"},{"title":"식의약 데이터 포털","url":"https://data.mfds.go.kr/"},{"title":"식품의약품안전평가원","url":"https://www.nifds.go.kr/"},{"title":"의약품안전나라 > 고객지원 > 통합자료실 > eCTD민원서식작성기","url":"https://nedrug.mfds.go.kr/bbs/43"}]
Based on the search results, I found information about the key components of your query:
1. **RISS (학술연구정보서비스)**: RISS is an academic research information service that collects and provides thesis content and academic journal articles to support research.
2. **NeDrug (의약품안전나라)**: This is a drug information search service that provides information on drugs, products, manufacturers, drug advertisements, and specification standards. It is managed by the Ministry of Food and Drug Safety (식품의약품안전처).
3. **Data Portal (식의약 데이터 포털)**: The MFDS also operates a pharmaceutical and food data portal that provides authorized drug and medical device information in various data formats (XML, JSON).
Your search query appears to be about a thesis or research system related to automating the collection of pharmaceutical approval information through web crawling from NeDrug and other MFDS systems. However, the search results don't contain specific information about a particular thesis project with that exact title. If you're looking for a specific thesis or academic paper on this topic, you might need to search directly on the RISS database or provide more specific details about the research.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #17] Leotta ROBULA+ robust XPath locators algorithm web element fragility 2016
Web search results for query: "Leotta ROBULA+ robust XPath locators algorithm web element fragility 2016"
Links: [{"title":"Robula+: An algorithm for generating robust XPath locators for web testing - Technical University of Munich","url":"https://portal.fis.tum.de/en/publications/robula-an-algorithm-for-generating-robust-xpath-locators-for-web-"},{"title":"Robula+: an algorithm for generating robust XPath locators for web testing - Leotta - 2016 - Journal of Software: Evolution and Process - Wiley Online Library","url":"https://onlinelibrary.wiley.com/doi/10.1002/smr.1771"},{"title":"Robula+: An algorithm for generating robust XPath locators for web testing | Request PDF","url":"https://www.researchgate.net/publication/299336358_Robula_An_algorithm_for_generating_robust_XPath_locators_for_web_testing"},{"title":"GitHub - cyluxx/robula-plus: An algorithm for generating robust XPath locators for web testing. · GitHub","url":"https://github.com/cyluxx/robula-plus"},{"title":"GitHub - ZeusFSX/robula-plus: An algorithm for generating robust XPath locators for web testing. Python version. · GitHub","url":"https://github.com/ZeusFSX/robula-plus"},{"title":"Reducing Web Test Cases Aging by Means of Robust XPath Locators | Request PDF","url":"https://www.researchgate.net/publication/266206039_Reducing_Web_Test_Cases_Aging_by_Means_of_Robust_XPath_Locators"},{"title":"[PDF] Robula+: an algorithm for generating robust XPath locators for web testing | Semantic Scholar","url":"https://www.semanticscholar.org/paper/Robula+:-an-algorithm-for-generating-robust-XPath-Leotta-Stocco/8d184cf0e7af185f7fe9eedaf66f2f6e8edf4091"},{"title":"Robula+: an algorithm for generating robust XPath locators for web testing: Journal of Software: Evolution and Process: Vol 28, No 3","url":"https://dl.acm.org/doi/10.1002/smr.1771"},{"title":"Erratum: Leveraging Flexible Tree Matching to Repair Broken Locators in Web Automation Scripts","url":"https://arxiv.org/pdf/2106.04916"}]
Based on the search results, here's what I found about the ROBULA+ algorithm:
## Overview
ROBULA+ is a novel algorithm able to generate robust XPath-based locators – locators that are likely to work correctly on new releases of the web application. The research was conducted by Leotta, Stocco, Ricca, and Tonella.
## Publication Details
The work was published in the Journal of Software: Evolution and Process in 2016, Volume 28, Number 3, pages 177-204.
## Problem It Addresses
One of the major costs for evolving test code is the manual effort necessary to repair broken web page element locators – lines of source code identifying the web elements (e.g. form fields and buttons) to interact with. The adoption of automated web testing brings advantages but also novel problems, among which the test code fragility problem, where existing test code may easily break during web application evolution.
## Performance Results
Results show that XPath locators produced by Robula+ are by far the most robust, reducing the locators' fragility on average by 90% with respect to absolute locators and by 63% with respect to Selenium IDE locators.
## Significance
The ROBULA+ algorithm is considered the state of the art algorithm for automatically generating robust XPath expressions.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #18] LLM generated XPath wrapper deterministic extraction hybrid pipeline paper 2025 "wrapper" "large language model" web data extraction
Web search results for query: "LLM generated XPath wrapper deterministic extraction hybrid pipeline paper 2025 "wrapper" "large language model" web data extraction"
Links: [{"title":"A Hybrid LLM and Supervised Model Pipeline for Polymer Property Extraction from Tables in Scientific Literature - ACL Anthology","url":"https://aclanthology.org/2025.wasp-main.11/"},{"title":"DELM: a Python toolkit for Data Extraction with Language Models","url":"https://arxiv.org/pdf/2509.20617"},{"title":"(PDF) A Reliability Evaluation of Hybrid Deterministic-LLM Based Approaches for Academic Course Registration PDF Information Extraction","url":"https://www.researchgate.net/publication/401715527_A_Reliability_Evaluation_of_Hybrid_Deterministic-LLM_Based_Approaches_for_Academic_Course_Registration_PDF_Information_Extraction"},{"title":"Prompt2DAG: A Modular Methodology for LLM-Based Data Enrichment Pipeline Generation","url":"https://arxiv.org/html/2509.13487v1"},{"title":"RATE: An LLM-Powered Retrieval Augmented Generation Technology-Extraction Pipeline","url":"https://arxiv.org/html/2507.21125v1"},{"title":"AXE: Low-Cost Cross-Domain Web Structured Information Extraction","url":"https://arxiv.org/html/2602.01838"},{"title":"Tabular PDF Information Extraction with Local LLMs and Layout-Aware Parsing: A Reliability Evaluation","url":"https://arxiv.org/pdf/2604.00003"}]
I found several relevant papers related to LLM-based extraction pipelines with hybrid approaches. Here are the key results:
## Most Relevant Findings:
**AXE: Low-Cost Cross-Domain Web Structured Information Extraction** - AXE (Adaptive X-Path Extractor) is a filter that removes boilerplate and irrelevant HTML page parts to produce query-relevant text that smaller LLMs can use to generate structured JSON output. This paper directly addresses web data extraction using XPath expressions combined with LLMs.
**Hybrid Deterministic-LLM Approaches for PDF Information Extraction** - A study evaluated information extraction approaches using three strategies: LLM-only, Hybrid Deterministic-LLM (regex + LLM), and a Camelot-based pipeline with LLM fallback, showing that the hybrid approach can improve efficiency compared to LLM-only, especially for deterministic metadata.
**Prompt2DAG: A Modular Methodology for LLM-Based Data Enrichment** - The deterministic Template-based method achieved the highest success rate (92.3%), while among generative methods, the Hybrid approach delivered a 78.5% success rate with the highest quality scores across all metrics.
**DELM: Python Toolkit for Data Extraction with Language Models** - The system leverages concurrent execution, retry logic, and deterministic caching keyed to the fully rendered prompt, schema, model, and generation parameters.
These papers demonstrate the effectiveness of combining deterministic extraction methods with LLMs for improved reliability and efficiency in structured data extraction tasks.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [FETCH #12] https://www.vldb.org/pvldb/vol4/p219-dalvi.pdf
**ASK:** Summarize: title, authors, venue, year. Key idea about generating robust wrappers/XPath from noisy annotations, and how robustness to page changes is measured.
connect ECONNREFUSED 162.214.151.244:443
## [FETCH #13] https://www.nowpublishers.com/article/Details/INR-017
**ASK:** Give title, authors, year, volume, issue, pages, DOI, abstract and table of contents (sections) of this Foundations and Trends in IR article on Web Crawling.
The server returned HTTP 403 Forbidden.
The response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.
## [FETCH #14] https://www.semanticscholar.org/paper/Effective-page-refresh-policies-for-Web-crawlers-Cho-Garcia-Molina/07523653232201428925b335ee5efd67ec54765e
**ASK:** Give abstract, authors, venue, year, and key findings (Poisson model, freshness/age, uniform vs proportional refresh policy).
I appreciate your detailed instructions, but I notice that the web page content you've provided appears to be empty or blank (just dashes with no actual text between them).
To provide the abstract, authors, venue, year, and key findings you're requesting—specifically regarding the Poisson model, freshness/age considerations, and uniform versus proportional refresh policies—I would need the actual content of the webpage.
Could you please share the complete webpage content or provide the URL/document you'd like me to analyze? Once you do, I'll be happy to extract and summarize that information while adhering to your specified constraints.
## [FETCH #15] https://www.semanticscholar.org/paper/The-Evolution-of-the-Web-and-Implications-for-an-Cho-Garcia-Molina/ed7087560de484b922e316874a9076376a2a0186
**ASK:** Give abstract, authors, venue, year, and key findings about page change rates and incremental crawler design.
I appreciate your request, but the web page content provided appears to be empty or blank. There is no actual article text, abstract, author information, venue details, year, or findings about page change rates and incremental crawler design for me to analyze.
To help you effectively, please provide:
- The actual web page content or article text
- Or a link to the specific research paper you'd like summarized
Once you share the content, I'll be happy to extract the abstract, authors, venue, year, and key findings while adhering to your specified guidelines about character limits for quotes and proper attribution.
## [FETCH #16] https://www.cs.cornell.edu/courses/cs685/2002fa/mercator.pdf
**ASK:** Summarize this report: title, authors, year. Architecture: URL frontier with front-end/back-end queues, politeness (one connection per host), content-seen test via fingerprints, URL-seen test, DNS, checkpointing, extensibility via protocol/processing modules.
# Report Summary
**Title:** Appears to be a technical document on web crawler architecture
**Authors & Year:** The PDF metadata indicates creation date of September 26, 2001, but author names are not clearly visible in the provided content.
## Architecture Overview
The system implements a sophisticated web crawling infrastructure with these key components:
**URL Management:** A "frontier" system with dual-queue architecture separates URLs into front-end and back-end queues for efficient processing.
**Politeness Constraints:** The crawler maintains "one connection per host" to avoid overwhelming target servers, a standard practice in respectful crawling.
**Deduplication:** Two filtering mechanisms prevent redundant work—fingerprints identify previously seen content, while URL-seen tests track visited links.
**Supporting Infrastructure:** The design includes DNS resolution capabilities, checkpointing for fault tolerance, and an extensible framework supporting multiple protocols and processing modules.
This architecture reflects early 2000s best practices for large-scale web crawling, balancing crawl efficiency with server-friendly politeness policies.
[Binary content (application/pdf, 94KB) also saved to C:\Users\encep\.claude\projects\D--workspace-DMF-Crawler\c00474d0-f118-4917-817d-1c16591aefc7\tool-results\webfetch-1788353874771-5fu2oa.pdf]
## [FETCH #17] https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/33026.pdf
**ASK:** Summarize authors, venue, year, the simhash technique, the 64-bit fingerprint, Hamming distance k=3 threshold, and the algorithm for finding fingerprints differing in k bits. Mention Charikar 2002 reference.
I cannot provide a meaningful summary of this document. The content you've provided appears to be raw PDF binary data with embedded fonts and compression artifacts, rather than readable text.
To help you effectively, I would need:
1. **A text-extracted version** of the PDF, or
2. **The actual document title and authors** you're asking about, or
3. **A clearer source** with the research content
If you're researching SimHash fingerprinting techniques (which does relate to Charikar's 2002 work on locality-sensitive hashing), I'd recommend:
- Accessing the paper directly through academic databases (Google Scholar, ACM Digital Library)
- Copying the text content rather than binary PDF data
- Providing the paper's title or DOI for reference
Once you share readable content, I can provide the structured summary you've requested, respecting all your formatting and citation requirements.
[Binary content (application/pdf, 153.9KB) also saved to C:\Users\encep\.claude\projects\D--workspace-DMF-Crawler\c00474d0-f118-4917-817d-1c16591aefc7\tool-results\webfetch-1788353877548-psyt0q.pdf]
## [FETCH #18] https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART000881131
**ASK:** 논문 제목, 저자, 학술지명, 발행연도, 권호, 초록을 알려줘. 웹 사이트 컨텐츠 변경 모니터링 시스템의 구성(변경 감지 방법, 주기, 알림)을 요약해줘.
# 논문 정보
**제목:** 웹 사이트 컨텐츠 변경 모니터링 시스템 (The Monitoring System for Informing the Change of Contents on the Web Sites)
**저자:** 김원중, 조이기, 손철수
**학술지:** 한국정보통신학회논문지
**발행연도:** 2002
**권호:** 제6권 제4호 (pp. 505-512)
**초록:** 인터넷의 무한한 정보량으로 인해 사용자들이 관심 정보의 변경을 즉시 인식하기 어렵다는 문제를 다룬다. 본 연구는 "웹에서 변화된 정보를 자동적으로 감지하여 사용자에게 알려주는 정보변화 감시 기능"을 구현했다.
---
# 시스템 구성 요약
**세 가지 주요 구성 요소:**
1. **변경 감지 방법:** HTML 태그를 활용하여 웹 문서를 의미 있는 단위로 구조화하고 분류하는 방식을 채택했다.
2. **모니터링 주기:** 사용자가 정의 가능한 모니터링 주기를 설정할 수 있다.
3. **알림 체계:** 변경 발생 시 "알람이나 E-mail를 통하여 자동으로 통지"하는 방식으로 구현했다.
## [FETCH #19] https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART001648031
**ASK:** 논문 제목, 저자, 학술지명, 발행연도, 권호, 초록을 알려줘. 웹 게시판 모니터링과 알람 서비스의 구현 방식을 요약해줘.
# 논문 정보
**제목:** 실시간 웹 게시판 모니터링 및 모바일웹을 이용한 알람 서비스 개발
**저자:** 김종근, 심근호, 이요셉, 임영환
**학술지:** 디지털콘텐츠학회논문지 (Journal of Digital Contents Society)
**발행연도:** 2012
**권호:** 제13권 제1호 (pp. 1-11)
**초록 요약:**
웹 게시판의 정보를 실시간으로 감시하고 사용자에게 알려주는 기술 개발에 관한 연구입니다. 기존 방법들은 데이터베이스 직접 접근이나 개방 API 활용으로 모니터링했으나, 비공개 게시판 접근 불가와 실시간 알림 어려움이라는 문제가 있었습니다.
## 구현 방식
**핵심 혁신:**
저자들은 "비 규격화된 모바일 웹의 단점을 극복하는 기술"을 제시했습니다. 모바일 기기의 다양한 콘텐츠 규격 문제를 해결함으로써, 모니터링 같은 실시간 서비스에 모바일 웹을 효과적으로 활용할 수 있게 했습니다.
**주요 개선점:** 기존 이메일 기반 알림 대신 모바일 웹 플랫폼을 통해 언제 어디서나 접근 가능한 즉각적인 알림 서비스를 구현했습니다.
## [FETCH #20] https://scienceon.kisti.re.kr/srch/selectPORSrchArticle.do?cn=JAKO201909258120005
**ASK:** 논문 제목, 저자, 학술지명, 발행연도, 초록을 알려줘. 실시간 웹 크롤링 분산 모니터링 시스템의 구성 요약.
# 논문 정보
**제목:** 실시간 웹 크롤링 분산 모니터링 시스템 설계 및 구현
(Design and Implementation of Real-time Web Crawling Distributed Monitoring System)
**저자:** 김영아, 김계희, 김현주, 김창근 (경남과학기술대학교 컴퓨터공학과)
**학술지:** 융합정보논문지 (Journal of Convergence for Information Technology)
**발행연도:** 2019년
**권호:** Vol. 9, No. 1, pp. 45-53
---
## 시스템 구성 요약
이 논문에서 제안하는 R-WCMS(웹 크롤링 분산 모니터링 시스템)는 다음과 같이 구성됩니다:
**핵심 기능:**
- 제한된 웹사이트의 실시간 정보 수집
- 수집 시간 예측을 통한 효율화
- 병렬 시스템을 통한 데이터 저장
**기술 스택:**
- Apache Kafka (메시지 처리)
- Apache Spark Streaming (실시간 데이터 처리)
- Hadoop (병렬 시스템)
**성과:** 기존 방식 대비 웹 수집 시간이 15-17% 단축되었습니다.
## [FETCH #21] https://arxiv.org/abs/2502.02430
**ASK:** Give title, authors, date, abstract summary. How does the crawling algorithm use noisy change-indicating signals, and what is the relationship to Poisson change models / Cho & Garcia-Molina?
# Paper Summary
**Title:** A Scalable Crawling Algorithm Utilizing Noisy Change-Indicating Signals
**Authors:** Róbert Busa-Fekete, Julian Zimmert, András György, Linhai Qiu, Tzu-Wei Sung, Hao Shen, Hyomin Choi, Sharmila Subramaniam, Li Xiao
**Date:** Submitted February 4, 2025; revised March 20, 2025
**Abstract Summary:**
The paper addresses web cache maintenance by developing an algorithm that incorporates noisy side information (such as sitemaps and CDN signals) about content changes. The approach "uses the noisy side information in an optimal way under mild assumptions" while enabling distributed deployment without central computation overhead.
## Relationship to Poisson Models
The work extends prior research by Azar et al. (2018), which assumed "change and request events, resp., to each web page follow independent Poisson processes" to derive optimal scheduling policies. This paper moves beyond that idealized framework by acknowledging that real-world change signals contain false positives and miss actual updates.
The algorithm addresses practical limitations of the Poisson assumption by handling signal noise while maintaining fair performance across pages with varying information quality. It automatically adapts to bandwidth changes without centralized recomputation.
Note: The document references Azar et al. 2018 rather than Cho & Garcia-Molina specifically, though both contributed foundational work to web crawling optimization.
## [FETCH #22] https://arxiv.org/abs/2602.01838
**ASK:** Give title, authors, date, abstract summary. How does AXE combine XPath-based filtering with small LLMs for structured extraction? Any numbers on cost/accuracy?
# AXE: Low-Cost Cross-Domain Web Structured Information Extraction
**Title:** AXE: Low-Cost Cross-Domain Web Structured Information Extraction
**Authors:** Abdelrahman Mansour, Khaled W. Alshaer, Moataz Elsaban
**Date:** Submitted February 2, 2026 (revised March 30, 2026)
## Abstract Summary
The paper addresses the challenge of extracting web data without relying on brittle manual rules or expensive large language models. AXE introduces an approach that "rethinking this process by treating the HTML DOM as a tree that needs pruning rather than just a wall of text to be read."
## How AXE Works
The system combines three key components:
1. **DOM Pruning:** A specialized mechanism strips away boilerplate and irrelevant HTML nodes, creating condensed, high-quality context
2. **Small LLM:** Uses a 0.6 billion parameter model to generate structured outputs from the pruned content
3. **Grounded XPath Resolution (GXR):** Ensures every extracted data point is "physically traceable to a source node," maintaining accountability
## Performance & Cost
The results demonstrate strong performance: **88.1% F1 score on the SWDE dataset**, outperforming larger, fully-trained models in zero-shot evaluation. The minimal footprint (0.6B parameters) implies substantially lower computational costs compared to standard large language model approaches.
Code and adaptors are publicly available via GitHub.
## [FETCH #23] https://github.com/cyluxx/robula-plus
**ASK:** Summarize README: what the library does, language, how to use (API), license, reference to Leotta et al. 2016 paper.
# Robula+ Library Summary
**Purpose:**
Robula+ generates robust XPath locators for web testing that remain reliable across application updates, reducing locator fragility by 90% compared to absolute XPath and 63% versus Selenium IDE locators.
**Language:**
TypeScript/JavaScript implementation.
**Core API:**
- `getRobustXPath(element, document)` — produces an optimized XPath string
- `getElementByXPath(xPath, document)` — retrieves elements using XPath
- `uniquelyLocate(xPath, element, document)` — validates XPath specificity
**Installation:**
Requires Node.js. Clone the repository, run `npm install`, then `npm run build` to generate the compiled library folder.
**License:**
"The License of this code needs some clarification, so until then there will be no public install package available."
**Academic Reference:**
Based on Maurizio Leotta, Andrea Stocco, Filippo Ricca, and Paolo Tonella's 2016 paper in the Journal of Software: Evolution and Process (JSEP), Volume 28, Issue 3. The TypeScript implementation was created by Cyluxx.
## [FETCH #24] https://github.com/EZ-hwh/AutoScraper
**ASK:** Summarize README: what the repo does, language, how scrapers are generated (XPath action sequences?), datasets (SWDE), stars if visible, license.
# AutoScraper Repository Summary
**Purpose:** AutoScraper is the official implementation of a research paper on automatically generating web scrapers using AI agents that progressively understand webpage structures.
**Language:** Python (with requirements.txt for dependencies)
**Scraper Generation Method:** The system uses a "reflexion" pattern with large language models (ChatGPT, GPT-4) to generate scrapers. Users run `crawler_generation.py` to create scrapers, then `crawler_extraction.py` executes information extraction. The exact mechanism (whether XPath or another method) isn't detailed in the README.
**Datasets:** Primary evaluation uses the SWDE (Structured Web Data Extraction) benchmark, with additional datasets mentioned (DS1, Klarna).
**Repository Stats:** 492 stars, 45 forks, 12 watchers
**License:** Apache 2.0
**Status:** The project notes several TODOs, including adapting for real-world websites and creating a public demo website. Code appears research-focused rather than production-ready.
## [FETCH #25] https://www.semanticscholar.org/paper/On-the-resemblance-and-containment-of-documents-Broder/8addb1718c2bc6bbb0d82cd1a57b41198bf65965
**ASK:** Give abstract, author, venue, year and the key ideas: shingling, resemblance (Jaccard), containment, min-wise independent permutations sketch.
I appreciate your request, but the web page content provided appears to be empty—there's no actual text between the dashes to analyze.
To help you extract information about **shingling, resemblance (Jaccard), containment, and min-wise independent permutations sketch**, I would need:
1. A valid URL or
2. The actual webpage content pasted into your message
These concepts are typically associated with foundational computer science papers on near-duplicate detection and similarity estimation (often attributed to work from the late 1990s-early 2000s). Once you provide the source material, I can extract:
- **Abstract**
- **Author(s)**
- **Venue** and **Year**
- **Key ideas** related to those four techniques
Please share the webpage content or document, and I'll provide a concise analysis following your guidelines.
## [FETCH #26] http://www.vldb.org/conf/2001/P109.pdf
**ASK:** Is this the RoadRunner paper by Crescenzi, Mecca, Merialdo (VLDB 2001)? Summarize the approach: union-free regular expressions, ACME matching, comparing two pages of same class to infer a wrapper/template.
I cannot reliably summarize this document based on the provided content. What you've shared appears to be raw PDF binary data and embedded font definitions rather than readable text content. The payload consists primarily of:
- PDF structure metadata (objects, cross-reference tables)
- Compressed font streams (CMTI10, CMR12, CMBX12, etc.)
- Encoded image data
- Flate-compressed content streams
To accurately assess whether this is the RoadRunner paper by Crescenzi, Mecca, and Merialdo (VLDB 2001) and summarize their approach regarding union-free regular expressions and template inference, I would need:
1. **Extracted readable text** from the PDF, or
2. **A text-based version** of the paper
If you can provide the document in a more accessible format (plain text, HTML, or a properly extracted PDF text version), I'd be happy to confirm the paper's identity and summarize their methodology for inferring wrappers through page comparison analysis.
[Binary content (application/pdf, 347KB) also saved to C:\Users\encep\.claude\projects\D--workspace-DMF-Crawler\c00474d0-f118-4917-817d-1c16591aefc7\tool-results\webfetch-1788353892760-w6ajid.pdf]
## [FETCH #27] https://github.com/internetarchive/heritrix3
**ASK:** Summarize the README: what Heritrix is, language, license, key architecture concepts (frontier, politeness, crawl jobs, WARC output), links to documentation.
# Heritrix Summary
**What It Is**
Heritrix is the Internet Archive's open-source web crawler designed for "archival-quality" collection of digital content at web scale. The name derives from an archaic term for heiress, reflecting its mission to preserve cultural artifacts for future generations.
**Language & License**
Built in Java, Heritrix is distributed under the Apache License 2.0, with some files potentially subject to alternative licenses noted in the included LICENSE file.
**Key Architecture Concepts**
The crawler incorporates several important design principles:
- **Politeness & Respect**: It honors `robots.txt` exclusion directives and META nofollow tags, allowing operators to configure crawl load policies and user-agent identification for site communication.
- **Crawl Jobs**: Configuration-based approach to organizing discrete crawling operations with customizable parameters.
- **WARC Output**: Generates Web ARChive format files for storing crawled content and metadata.
- **Frontier Management**: Core queuing system managing URL discovery and prioritization during crawls.
**Documentation**
The project provides extensive resources including getting started guides, operational manuals, configuration references, REST API documentation, and JavaDoc across multiple modules (engine, commons, modules, contrib).
## [SEARCH #19] Azar Horvitz Lubetzky Peres Shahaf "Tractable near-optimal policies for crawling" PNAS 2018
Web search results for query: "Azar Horvitz Lubetzky Peres Shahaf "Tractable near-optimal policies for crawling" PNAS 2018"
Links: [{"title":"Tractable near-optimal policies for crawling | PNAS","url":"https://www.pnas.org/doi/10.1073/pnas.1801519115"},{"title":"Tractable near-optimal policies for crawling - PMC","url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC6094111/"},{"title":"(PDF) Tractable near-optimal policies for crawling","url":"https://www.researchgate.net/publication/326564976_Tractable_near-optimal_policies_for_crawling"},{"title":"Eric Horvitz: Publications","url":"http://erichorvitz.com/abstracts.htm"},{"title":"Eric Horvitz: Publications by topic area","url":"https://www.erichorvitz.com/abstracts_by_topic.htm"},{"title":"Eric Horvitz: Selected publications by topic area","url":"https://erichorvitz.com/selected_refs_by_topic.htm"},{"title":"Tractable near-optimal policies for crawling - PubMed","url":"https://pubmed.ncbi.nlm.nih.gov/30038026/"},{"title":"COMPUTER SCIENCES Tractable near-optimal policies for crawling","url":"https://erichorvitz.com/Crawl_1801519115.full.pdf"},{"title":"Learning to Crawl","url":"https://arxiv.org/pdf/1905.12781"}]
I found the paper you're searching for! Here are the key details:
**Paper Information:**
The paper "Tractable near-optimal policies for crawling" by Yossi Azar, Eric Horvitz, Eyal Lubetzky, Yuval Peres, and Dafna Shahaf was published in PNAS on July 23, 2018, Volume 115, Issue 32, pages 8099–8103.
**Author Affiliations:**
- Yossi Azar: Department of Computer Science, Tel-Aviv University, Tel-Aviv, Israel
- Eric Horvitz and Yuval Peres: Microsoft Research, Redmond, WA
- Eyal Lubetzky: Courant Institute of Mathematical Sciences, New York University, New York, NY
- Dafna Shahaf: School of Computer Science, Hebrew University, Jerusalem, Israel
**Research Focus:**
The paper presents a tractable algorithm that provides a near-optimal solution to the crawling problem, a fundamental challenge at the heart of web search. The problem involves maintaining a local cache of constantly changing pages in web crawlers and proxy servers with limited resources for polling, with the goal of devising a policy that maximizes the utility of served pages that are up to date.
The paper is available at the PNAS website (https://www.pnas.org/doi/10.1073/pnas.1801519115).
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #20] Kushmerick "Wrapper induction for information extraction" IJCAI 1997 Weld Doorenbos LR wrapper
Web search results for query: "Kushmerick "Wrapper induction for information extraction" IJCAI 1997 Weld Doorenbos LR wrapper"
Links: [{"title":"Wrapper maintenance: a machine learning approach: Journal of Artificial Intelligence Research: Vol 18, No 1","url":"https://dl.acm.org/doi/abs/10.5555/1622420.1622425"},{"title":"[PDF] Wrapper Induction for Information Extraction | Semantic Scholar","url":"https://www.semanticscholar.org/paper/Wrapper-Induction-for-Information-Extraction-Kushmerick-Weld/f9e7402ad740b73cc0bb64178f86df3478c3aaf5"},{"title":"Automatic Wrappers for Large Scale Web Extraction Nilesh Dalvi Yahoo! Research","url":"https://arxiv.org/pdf/1103.2406"},{"title":"Wrapping Web Information Providers by Transducer Induction | SpringerLink","url":"https://link.springer.com/chapter/10.1007/3-540-44795-4_6"},{"title":"The Wrapper Induction Environment Nicholas Kushmerick Dublin City University","url":"https://cdn.aaai.org/Workshops/1998/WS-98-10/WS98-10-022.pdf"},{"title":"Wrapper (data mining)","url":"https://en.wikipedia.org/wiki/Wrapper_(data_mining)"},{"title":"Publications by Daniel S. Weld","url":"https://homes.cs.washington.edu/~weld/pubs.html"},{"title":"Visual and interactive wrapper generation, automated information extraction from Web pages, and translation into XML","url":"https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/7581170"},{"title":"METHOD AND APPARATUS FOR ELECTRONICALLY EXTRACTING APPLICATION SPECIFIC MULTIDIMENSIONAL INFORMATION FROM DOCUMENTS SELECTED FROM A SET OF DOCUMENTS ELECTRONICALLY EXTRACTED FROM A LIBRARY OF ELECTRONICALLY SEARCHABLE DOCUMENTS","url":"https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/6965900"},{"title":"Regression testing for wrapper maintenance Nicholas Kushmerick","url":"https://cdn.aaai.org/AAAI/1999/AAAI99-011.pdf"}]
Based on the search results, I found information about the paper you're looking for:
Kushmerick, N., Weld, D. S., & Doorenbos, R. B. (1997). Wrapper induction for information extraction. In Proceedings of the Intl. Joint Conference on Artificial Intelligence (IJCAI), pp. 729-737.
This work introduces wrapper induction, a method for automatically constructing wrappers, and identifies hlrt, a wrapper class that is efficiently learnable, yet expressive enough to handle 48% of a recently surveyed sample of Internet resources. The authors use PAC analysis to bound the problem's sample complexity, and show that the system degrades gracefully with imperfect labeling knowledge.
An example of such a system is the Wien wrapper induction environment (Nicholas Kushmerick, Daniel S. Weld, Robert B. Doorenbos, "Wrapper Induction for Information Extraction", Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, IJCAI 97, Nagoya, Japan, Aug. 23-29, 1997).
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #21] Kolobov Peres Lubetzky Horvitz "Staying up to date with online content changes using reinforcement learning for scheduling" NeurIPS 2019
Web search results for query: "Kolobov Peres Lubetzky Horvitz "Staying up to date with online content changes using reinforcement learning for scheduling" NeurIPS 2019"
Links: [{"title":"Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling","url":"https://papers.nips.cc/paper/2019/hash/ad13a2a07ca4b7642959dc0c4c740ab6-Abstract.html"},{"title":"Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling | OpenReview","url":"https://openreview.net/forum?id=ByxjGvuKoE"},{"title":"Reinforcement Learning Papers Accepted to NeurIPS 2019 | endtoend.ai","url":"https://www.endtoend.ai/explore/neurips2019-rl/"},{"title":"NeurIPS 2019","url":"https://nips.cc/Conferences/2019/ScheduleMultitrack?event=14033"},{"title":"A Scalable Crawling Algorithm Utilizing Noisy Change-Indicating Signals","url":"https://arxiv.org/pdf/2502.02430"},{"title":"Online Learning for Active Cache Synchronization","url":"https://arxiv.org/pdf/2002.12014"},{"title":"Look back, look around: a systematic analysis of effective predictors for new outlinks in focused Web crawling","url":"https://arxiv.org/pdf/2111.05062"},{"title":"Learning to Crawl","url":"https://arxiv.org/pdf/1905.12781"},{"title":"NeurIPS 2020","url":"https://nips.cc/Conferences/2020/ScheduleMultitrack?event=17616"}]
I found the paper! Here are the search results for your query:
## Paper Details
The paper "Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling" by Andrey Kolobov, Yuval Peres, Cheng Lu, and Eric J Horvitz was published at Advances in Neural Information Processing Systems 32 (NeurIPS 2019).
## Paper Summary
The paper addresses the problem of services that rely on online information and need to continually keep track of remote content changes by explicitly requesting content updates from remote sources (e.g., web pages).
The authors propose a novel optimization objective for this setting that has several practically desirable properties, and efficient algorithms for it with optimality guarantees even in the face of mixed content change observability and initially unknown change model parameters.
Experiments on 18.5M URLs crawled daily for 14 weeks show significant advantages of this approach over prior art.
## Where to Find It
The paper is available at:
- **NeurIPS official proceedings**: https://papers.nips.cc/paper/2019/hash/ad13a2a07ca4b7642959dc0c4c740ab6-Abstract.html
- **OpenReview**: https://openreview.net/forum?id=ByxjGvuKoE
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #22] "table extraction" HTML web tables structured data Cafarella WebTables VLDB 2008
Web search results for query: ""table extraction" HTML web tables structured data Cafarella WebTables VLDB 2008"
Links: [{"title":"Processing Web Tables","url":"https://hpi.de/naumann/teaching/teaching/ss-19/processing-web-tables.html"},{"title":"WebTables: Exploring the Power of Tables on the Web Michael J. Cafarella ∗","url":"http://www.vldb.org/pvldb/vol1/1453916.pdf"},{"title":"Schema Extraction for Tabular Data on the Web ∗ Marco D. Adelfio Hanan Samet","url":"http://www.vldb.org/pvldb/vol6/p421-adelfio.pdf"},{"title":"WebTables: exploring the power of tables on the web: Proceedings of the VLDB Endowment: Vol 1, No 1","url":"https://dl.acm.org/doi/10.14778/1453856.1453916"},{"title":"(PDF) WebTables: Exploring the power of tables on the web","url":"https://www.researchgate.net/publication/220538521_WebTables_Exploring_the_power_of_tables_on_the_web"},{"title":"Identifying Web Tables: Supporting a Neglected Type of Content on the Web | Springer Nature Link","url":"https://link.springer.com/chapter/10.1007/978-3-319-24543-0_4"},{"title":"On Extracting Data from Tables that are Encoded using HTML","url":"https://arxiv.org/pdf/1903.08305"},{"title":"Identifying Web Tables - Supporting a Neglected Type of Content on the Web","url":"https://arxiv.org/pdf/1503.06598"},{"title":"An Annotated Corpus of Webtables for Information Extraction Tasks","url":"https://arxiv.org/pdf/2008.07680"},{"title":"WEB TABLE EXTRACTION, RETRIEVAL AND AUGMENTATION: A SURVEY A PREPRINT","url":"https://arxiv.org/pdf/2002.00207"}]
The search results provide comprehensive information about table extraction from HTML and the seminal WebTables work. Here's what I found:
## WebTables: The Landmark Study
In a large-scale crawling effort in 2008, Cafarella et al. extracted 14.1 billion tables from billions of HTML webpages. The researchers used statistical classification techniques to find the estimated 154M that contain high-quality relational data.
## The Publication
The paper by Cafarella, M. J., Halevy, A., Wang, D. Z., Wu, E., & Zhang, Y. (2008) titled "Webtables: exploring the power of tables on the web" was published in the Proceedings of the VLDB Endowment, 1(1), 538-549.
## Key Context
While many webtables are used for layout purposes only, there are still much more tables that contain high-quality and structured information. Cafarella et al. estimate that 154 million of the 14.1 billion tables contain relational data, i.e., database-alike tables.
This work was foundational for web table research and demonstrated that the web contains massive amounts of structured data in HTML table format that could be automatically extracted and analyzed.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #23] Martin Fowler Event Sourcing snapshot vs event log change data capture pattern
Web search results for query: "Martin Fowler Event Sourcing snapshot vs event log change data capture pattern"
Links: [{"title":"Event Sourcing | arc42 Quality Model","url":"https://quality.arc42.org/approaches/event-sourcing"},{"title":"Event Sourcing","url":"https://martinfowler.com/eaaDev/EventSourcing.html"},{"title":"Change Data Capture: From Batch to Real-Time | Capital One","url":"https://www.capitalone.com/tech/software-engineering/batch-to-real-time-with-change-data-capture/"},{"title":"Event Sourcing Pattern - Azure Architecture Center | Microsoft Learn","url":"https://learn.microsoft.com/en-us/azure/architecture/patterns/event-sourcing"},{"title":"The Many Meanings of Event-Driven Architecture - Martin Fowler (GOTO 2017) - HackMD","url":"https://hackmd.io/@pierodibello/The-Many-Meanings-of-Event-Driven-Architecture"},{"title":"My notes on the talk \"The Many Meanings of Event-Driven Architecture\" by Martin Fowler (GOTO 2017) · GitHub","url":"https://gist.github.com/xpepper/36beda855540b0c1dde6c4c417dafec9"},{"title":"Understanding Event Sourcing: Key Principles and Benefits","url":"https://www.baytechconsulting.com/blog/event-sourcing-explained-2025"},{"title":"Event Sourcing Explained: Capturing State Changes at Scale - DevX","url":"https://www.devx.com/technology/event-sourcing-explained-capturing-state-changes-at-scale/"},{"title":"event sourcing","url":"https://www.gatlin.io/content/event-sourcing"}]
I found search results covering Event Sourcing, snapshots, and Change Data Capture. Here's what the results reveal about these concepts:
## Event Sourcing
Event Sourcing captures all changes to an application state as a sequence of events. Every state change appends to an immutable log as a domain event — OrderPlaced, PaymentCaptured — and current state is computed by replay.
## Snapshots vs Event Log
Snapshots are an optimization, not a replacement for the eventstream. Once a certain number of events are produced, a snapshot event record is created, which provides a current state view and saves consumers time when replaying events. Once aggregates accumulate hundreds or thousands of events, snapshot state periodically and replay only new events.
## Change Data Capture Pattern
Change data capture retrofits an event stream onto a CRUD store — row deltas without domain intent. CDC is a way to generate state changes as events from a database, while Event Sourcing is a pattern that captures individual events that can be replayed to get current state.
The key distinction is that Event Sourcing is an application-level pattern focused on domain events, while Change Data Capture works at the database level capturing row-level changes without semantic meaning.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [CMD] cd "C:/Users/encep/.claude/projects/D--workspace-DMF-Crawler/c00474d0-f118-4917-817d-1c16591aefc7/tool-results" && ls -la *.pdf && python -c "import pypdf,sys;print('pypdf',pypdf.__version__)" 2>&1; python - <<'EOF'
import glob,os
try:
from pypdf import PdfReader
except Exception as e:
print
…[truncated 315 chars]
```
-rw-r--r-- 1 encep 197609 194487 Sep 2 21:56 webfetch-1788353809737-s6vaqp.pdf
-rw-r--r-- 1 encep 197609 96301 Sep 2 21:57 webfetch-1788353874771-5fu2oa.pdf
-rw-r--r-- 1 encep 197609 157615 Sep 2 21:57 webfetch-1788353877548-psyt0q.pdf
-rw-r--r-- 1 encep 197609 355286 Sep 2 21:58 webfetch-1788353892760-w6ajid.pdf
pypdf 4.3.1
===== webfetch-1788353809737-s6vaqp.pdf 5 pages
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```
## [FETCH #28] https://api.semanticscholar.org/graph/v1/paper/07523653232201428925b335ee5efd67ec54765e?fields=title,authors,year,venue,abstract,citationCount,externalIds
**ASK:** Return the JSON fields: title, authors, year, venue, abstract, citationCount, DOI.
The server returned HTTP 429 Too Many Requests.
The response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.
## [FETCH #29] https://api.semanticscholar.org/graph/v1/paper/ed7087560de484b922e316874a9076376a2a0186?fields=title,authors,year,venue,abstract,citationCount,externalIds
**ASK:** Return the JSON fields: title, authors, year, venue, abstract, citationCount, DOI.
The server returned HTTP 429 Too Many Requests.
The response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.
## [FETCH #30] https://api.semanticscholar.org/graph/v1/paper/8addb1718c2bc6bbb0d82cd1a57b41198bf65965?fields=title,authors,year,venue,abstract,citationCount,externalIds
**ASK:** Return the JSON fields: title, authors, year, venue, abstract, citationCount, DOI.
The server returned HTTP 429 Too Many Requests.
The response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.
## [FETCH #31] https://api.semanticscholar.org/graph/v1/paper/f9e7402ad740b73cc0bb64178f86df3478c3aaf5?fields=title,authors,year,venue,abstract,citationCount,externalIds
**ASK:** Return the JSON fields: title, authors, year, venue, abstract, citationCount, DOI.
The server returned HTTP 429 Too Many Requests.
The response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.
## [FETCH #32] https://api.semanticscholar.org/graph/v1/paper/search?query=RoadRunner+Towards+Automatic+Data+Extraction+from+Large+Web+Sites&fields=title,authors,year,venue,abstract,citationCount,externalIds&limit=3
**ASK:** Return the JSON results: for each paper title, authors, year, venue, abstract, citationCount, DOI.
The server returned HTTP 429 Too Many Requests.
The response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.
## [FETCH #33] https://api.semanticscholar.org/graph/v1/paper/search?query=An+Introduction+to+Heritrix+open+source+archival+quality+web+crawler&fields=title,authors,year,venue,abstract,citationCount&limit=3
**ASK:** Return the JSON results: for each paper title, authors, year, venue, abstract, citationCount.
The server returned HTTP 429 Too Many Requests.
The response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.
## [FETCH #34] https://api.semanticscholar.org/graph/v1/paper/search?query=Similarity+estimation+techniques+from+rounding+algorithms+Charikar&fields=title,authors,year,venue,abstract,citationCount,externalIds&limit=2
**ASK:** Return the JSON results: for each paper title, authors, year, venue, abstract, citationCount, DOI.
The server returned HTTP 429 Too Many Requests.
The response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.
## [FETCH #35] https://arxiv.org/abs/1103.2406
**ASK:** Give title, authors, venue (PVLDB vol 4?), date, abstract summary: robust wrappers from noisy annotations, robustness to temporal changes of page structure, how XPath robustness is evaluated.
# Paper Summary
**Title:** Automatic Wrappers for Large Scale Web Extraction
**Authors:** Nilesh Dalvi (Yahoo! Research), Ravi Kumar (Yahoo! Research), Mohamed Soliman (University of Waterloo)
**Venue:** Proceedings of the VLDB Endowment (PVLDB), Vol. 4, No. 4, pp. 219-230 (2011)
**Date:** March 12, 2011
**Abstract Summary:**
The researchers developed a framework enabling wrapper induction algorithms to handle noisy training data. This advancement allows unsupervised wrapper learning using automatically-generated, low-cost noisy annotations from dictionaries and regex patterns. By eliminating site-specific supervision requirements, the approach scales to web-wide information extraction while achieving superior accuracy compared to existing unsupervised methods. The system was deployed in production at Yahoo!.
**Note:** The provided webpage content does not include technical details about robustness to temporal page structure changes or specific XPath robustness evaluation methodologies. Those specifics would require access to the full paper PDF.
## [FETCH #36] https://api.semanticscholar.org/graph/v1/paper/8d184cf0e7af185f7fe9eedaf66f2f6e8edf4091?fields=title,authors,year,venue,abstract,citationCount,externalIds
**ASK:** Return the JSON fields: title, authors, year, venue, abstract, citationCount, DOI.
The server returned HTTP 429 Too Many Requests.
The response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.
## [FETCH #37] https://papers.nips.cc/paper/2019/hash/ad13a2a07ca4b7642959dc0c4c740ab6-Abstract.html
**ASK:** Give title, authors, venue, year, abstract, and the key idea: harmonic policy, complete vs incomplete change observability, learning change rates online, 18.5M URLs experiment.
# Paper Summary
**Title:** Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling
**Authors:** Andrey Kolobov, Yuval Peres, Cheng Lu, Eric J Horvitz
**Venue:** Advances in Neural Information Processing Systems 32 (NeurIPS 2019)
**Year:** 2019
**Abstract:** The paper addresses how web services maintain current information by periodically requesting updates from remote sources. It introduces "a novel optimization objective for this setting that has several practically desirable properties" and proposes algorithms with performance guarantees under uncertain change dynamics and incomplete initial knowledge.
**Key Ideas:**
The research focuses on scheduling content refreshes for web crawling and tracking. While the webpage excerpt doesn't explicitly detail the harmonic policy or complete versus incomplete observability mechanics, it indicates the approach handles "mixed content change observability and initially unknown change model parameters." The methodology appears to combine reinforcement learning with online parameter estimation to adaptively schedule updates based on observed change patterns.
**Experimental Validation:** The approach was evaluated on substantial real-world data: "18.5M URLs crawled daily for 14 weeks" with documented performance improvements compared to existing methods.
## [FETCH #38] https://pmc.ncbi.nlm.nih.gov/articles/PMC6094111/
**ASK:** Summarize: title, authors, venue, year, the crawling problem formulation (Poisson change rates, request rates, bandwidth constraint), the LambdaCrawl policy, and the near-optimality result.
# Summary: Tractable Near-Optimal Policies for Crawling
**Title:** "Tractable near-optimal policies for crawling"
**Authors:** Yossi Azar, Eric Horvitz, Eyal Lubetzky, Yuval Peres, and Dafna Shahaf
**Venue & Year:** Proceedings of the National Academy of Sciences (PNAS), July 2018
## Problem Formulation
The paper addresses web crawler cache maintenance: maintaining n dynamically changing pages while maximizing freshness of served content. The model incorporates:
- **Poisson change rates** (Δᵢ): probability each page changes per time unit
- **Request rates** (μᵢ): frequency users request each page
- **Bandwidth constraint** (R): total available polling resources
The objective maximizes freshness-weighted utility: serving up-to-date pages when requested.
## Solution Approach
Rather than a policy called "LambdaCrawl," the authors present **two efficient algorithms**:
- **Algorithm 1** solves discrete-time policies in O(n log n) time
- **Algorithm 2** solves continuous-time policies in O(n log n) time
Both find the unique optimal randomized policy by sorting pages by utility-to-change-rate ratios, then identifying which pages deserve zero allocation.
## Near-Optimality Result
The deterministic derandomized policy (Algorithm 3, using earliest-deadline-first scheduling) achieves "99% of the (numerically solved) optimal solution" in experiments, converting probabilistic allocations into practical cyclic refresh schedules.
## [FETCH #39] https://research.google/pubs/web-crawling/
**ASK:** Give title, authors, venue, year, abstract of this publication.
# Web Crawling Publication
**Title:** Web Crawling
**Authors:** Christopher Olston, Marc Najork
**Venue:** Foundations and Trends in Information Retrieval
**Year:** 2010
**Volume/Pages:** Vol. 4, pp. 175-246
**Abstract:** The webpage does not provide the full abstract text for this publication. Only the title, authors, venue, and publication details are visible in the provided content. To access the complete abstract, you would need to visit the full publication page or the Google Scholar link referenced on the page.
## [FETCH #40] https://martinfowler.com/eaaDev/EventSourcing.html
**ASK:** Summarize: author, date, definition of Event Sourcing, relationship to Application State snapshots, rebuild/replay, temporal query, and trade-offs mentioned.
# Event Sourcing Summary
**Author & Date:**
Martin Fowler published this article on December 12, 2005, as part of his Enterprise Application Architecture documentation.
**Definition:**
Event Sourcing involves capturing "all changes to an application state as a sequence of events." Rather than storing only current state, the system maintains a complete log of state-altering events that can be replayed to reconstruct any prior condition.
**Application State & Snapshots:**
The article distinguishes between two persisted elements: the event log and application state. Since state is fully derivable from events, snapshots serve as performance optimizations. Systems can cache snapshots on disk or in memory, replay recent events after crashes, and create new snapshots without disrupting operations.
**Rebuild & Replay:**
Complete rebuilds allow discarding current state and reconstructing it by rerunning all events from scratch. Event replay enables correcting past errors by reversing incorrect events and reprocessing the sequence with corrections.
**Temporal Query:**
This capability determines application state at any historical point by replaying events up to a specific moment in time.
**Key Trade-offs:**
Fowler emphasizes that Event Sourcing adds complexity—particularly with external system interactions, code changes, and event reversal logic. The pattern isn't a natural default choice; adopting it requires expecting meaningful returns through audit capabilities, debugging advantages, or architectural scalability benefits.
## [FETCH #41] https://developers.google.com/search/docs/crawling-indexing/robots/robots_txt
**ASK:** Does Google support crawl-delay? What does it say about unsupported rules, user-agent matching, caching, and file size limit (500 KiB)?
# Google's robots.txt Support and Specifications
**Crawl-delay Support:**
Google does not support the `crawl-delay` field. The documentation explicitly states: "Google supports the following fields (other fields such as `crawl-delay` aren't supported)."
**Unsupported Rules:**
The specification notes that "Rules other than `allow`, `disallow`, and `user-agent` are ignored by the robots.txt parser." This means unrecognized directives are simply disregarded during processing.
**User-agent Matching:**
Google applies the most specific user-agent match it finds. "Google's crawlers determine the correct group of rules by finding in the robots.txt file the group with the most specific user agent that matches the crawler's user agent."
**Caching:**
Google typically caches robots.txt files for extended periods: "Google generally caches the contents of robots.txt file for up to 24 hours, but may cache it longer in situations where refreshing the cached version isn't possible."
**File Size Limit:**
There is a strict maximum: "Google enforces a robots.txt file size limit of 500 kibibytes (KiB). Content which is after the maximum file size is ignored."
## [FETCH #42] https://docs.python.org/3/library/urllib.robotparser.html
**ASK:** List the RobotFileParser methods: set_url, read, can_fetch, crawl_delay, request_rate, site_maps, and their signatures and version notes.
# RobotFileParser Methods
Here are the methods of the `urllib.robotparser.RobotFileParser` class with their signatures and version notes:
## Core Methods
| Method | Signature | Purpose |
|--------|-----------|---------|
| `set_url` | `set_url(url)` | Sets the URL referring to a `robots.txt` file |
| `read` | `read()` | Reads the `robots.txt` URL and feeds it to the parser |
| `parse` | `parse(lines)` | Parses the lines argument |
## Query Methods
| Method | Signature | Purpose | Version |
|--------|-----------|---------|---------|
| `can_fetch` | `can_fetch(useragent, url)` | Returns `True` if the useragent is allowed to fetch the URL according to parsed `robots.txt` rules | — |
| `crawl_delay` | `crawl_delay(useragent)` | Returns the `Crawl-delay` parameter value from `robots.txt` for the useragent, or `None` if not found/invalid | Added in 3.6 |
| `request_rate` | `request_rate(useragent)` | Returns `RequestRate(requests, seconds)` named tuple from `robots.txt`, or `None` if not found/invalid | Added in 3.6 |
| `site_maps` | `site_maps()` | Returns a list of `Sitemap` parameter values from `robots.txt`, or `None` if not found/invalid | Added in 3.8 |
## Metadata Methods
| Method | Signature | Purpose |
|--------|-----------|---------|
| `mtime` | `mtime()` | Returns the time the `robots.txt` file was last fetched |
| `modified` | `modified()` | Sets the time the `robots.txt` file was last fetched to the current time |
## [SEARCH #24] wrapper induction "large language model" XPath generation SWDE zero-shot 2025 arXiv structured web extraction LLM-generated rules
Web search results for query: "wrapper induction "large language model" XPath generation SWDE zero-shot 2025 arXiv structured web extraction LLM-generated rules"
Links: [{"title":"(PDF) Automatic wrappers for large scale web extraction","url":"https://www.academia.edu/89369081/Automatic_wrappers_for_large_scale_web_extraction"},{"title":"AXE: Low-Cost Cross-Domain Web Structured Information Extraction","url":"https://arxiv.org/pdf/2602.01838"},{"title":"From one tree to a forest: a unified solution for structured web data extraction. | Request PDF","url":"https://www.researchgate.net/publication/221299838_From_one_tree_to_a_forest_a_unified_solution_for_structured_web_data_extraction"},{"title":"ZeroShotCeres: Zero-Shot Relation Extraction from Semi-Structured Webpages | Request PDF","url":"https://www.researchgate.net/publication/343297191_ZeroShotCeres_Zero-Shot_Relation_Extraction_from_Semi-Structured_Webpages"},{"title":"Automatic Wrappers for Large Scale Web Extraction | Request PDF","url":"https://www.researchgate.net/publication/50367565_Automatic_Wrappers_for_Large_Scale_Web_Extraction"},{"title":"Automatic XPath generation agents for vertical websites by LLMs | Journal of King Saud University Computer and Information Sciences | Springer Nature Link","url":"https://link.springer.com/article/10.1007/s44443-025-00071-w"},{"title":"AutoScraper: A Progressive Understanding Web Agent for Web Scraper Generation | alphaXiv","url":"https://www.alphaxiv.org/abs/2404.12753"}]
Based on the search results, I found several relevant papers on wrapper induction, large language models, and structured web extraction:
**Key Findings:**
1. **LLM-based XPath Generation**: A framework leverages multi-task decomposition strategy, enabling LLMs to learn robust XPath expressions from seed pages and apply them to unseen web pages, achieving state-of-the-art accuracy for vertical websites with minimal LLM interactions.
2. **Zero-shot Performance on SWDE**: AXE achieves state-of-the-art zero-shot performance on the SWDE dataset with an F1 score of 88.1%. Additionally, AutoScraper with GPT-4-Turbo achieves higher F1 scores than supervised learning methods on SWDE dataset, despite operating in zero-shot settings.
3. **Traditional Wrapper Induction**: XPath-wrapper induction involves generating tree traversal patterns using a subset of XPATH, and wrapper induction methods create a set of rules (wrappers) to transform unstructured input into structured output.
4. **LLM-based Approaches**: LLMs have enabled high-accuracy information extraction from individual pages, but the substantial costs associated with LLMs make this approach often economically impractical.
These results suggest an active research area combining traditional wrapper induction techniques with modern LLM-based approaches for structured web extraction tasks.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #25] Kushmerick "Regression testing for wrapper maintenance" AAAI 1999 wrapper verification RAPTURE
Web search results for query: "Kushmerick "Regression testing for wrapper maintenance" AAAI 1999 wrapper verification RAPTURE"
Links: [{"title":"(PDF) Wrapper Maintenance","url":"https://www.researchgate.net/publication/242026909_Wrapper_Maintenance"},{"title":"Wrapper Maintenance: A Machine Learning Approach","url":"https://arxiv.org/pdf/1106.4872"},{"title":"Wrapper Maintenance | SpringerLink","url":"https://link.springer.com/rwe/10.1007/978-1-4614-8265-9_1158"},{"title":"(PDF) Accurately and Reliably Extracting Data from the Web: A Machine Learning Approach","url":"https://www.researchgate.net/publication/220282644_Accurately_and_Reliably_Extracting_Data_from_the_Web_A_Machine_Learning_Approach"},{"title":"Wrapper Maintenance | Springer Nature Link","url":"https://link.springer.com/referenceworkentry/10.1007/978-0-387-39940-9_1158"},{"title":"Schema-guided wrapper maintenance for web-data extraction | Proceedings of the 5th ACM international workshop on Web information and data management","url":"https://dl.acm.org/doi/abs/10.1145/956699.956701"},{"title":"Wrapper maintenance: a machine learning approach: Journal of Artificial Intelligence Research: Vol 18, No 1","url":"https://dl.acm.org/doi/abs/10.5555/1622420.1622425"},{"title":"Regression testing for wrapper maintenance Nicholas Kushmerick","url":"https://cdn.aaai.org/AAAI/1999/AAAI99-011.pdf"},{"title":"Intelligent Self-repairable Web Wrappers | SpringerLink","url":"https://link.springer.com/chapter/10.1007/978-3-642-23954-0_26"}]
Based on the search results, here's what I found about this research:
Nicholas Kushmerick's paper "Regression testing for wrapper maintenance" was published in the Proceedings of the 14th National Conference on Artificial Intelligence (AAAI-1999).
The paper addresses wrapper verification and introduces the RAPTURE algorithm. Kushmerick's work addressed the problem of wrapper verification by proposing an algorithm called RAPTURE to verify that a wrapper correctly extracts data from a Web page.
In that work, each data field was described by a collection of global features, such as word count, average word length, and density of types. RAPTURE calculated the mean and variance of each feature's distribution over the training examples. Given a set of queries for which the wrapper output is known, RAPTURE generates a new result for each query and calculates the probability of generating the observed value for every feature. Individual feature probabilities are then combined to produce an overall probability that the wrapper has extracted data correctly.
This work is part of a broader research effort on wrapper maintenance, which is important because wrappers are specialized information extraction procedures used in information integration systems, and maintaining them is challenging when web page formats change.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #26] 나라장터 입찰공고 크롤링 알림 시스템 논문 KCI 2023 2024 공공 공고 모니터링 자동화
Web search results for query: "나라장터 입찰공고 크롤링 알림 시스템 논문 KCI 2023 2024 공공 공고 모니터링 자동화"
Links: [{"title":"나라**(국가종합전자조달시스템) 입찰공고 크롤링, 크롤링·스크래핑 포트폴리오 - 크몽","url":"https://kmong.com/portfolio/view/171486"},{"title":"나라장터 발주/입찰 공고 검색/알림 자체시스템구축 - 크몽","url":"https://kmong.com/gig/613778"},{"title":"나라장터 입찰공고 인공지능 검색모델 개발에 관한 연구","url":"https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002883147"},{"title":"KCI 국내학술지 인용색인 정보 포털입니다.","url":"https://www.kci.go.kr/kciportal/po/search/poArtiSearList.kci?sereId=000614"},{"title":"한국학술지인용색인(Korea Citation Index)","url":"https://www.kci.go.kr/kciportal/main.kci"},{"title":"2024년도 학술지평가 결과 공고","url":"https://www.kci.go.kr/kciportal/mobile/bbs/bbsNoticeView.kci?boardBean.bullScriSequ=000000039930"},{"title":"국가철도공단 KR전자조달시스템","url":"https://ebid.kr.or.kr/"},{"title":"KCI 국내 학술지 인용색인 정보 포털입니다.","url":"https://www.kci.go.kr/"},{"title":"Korea Citation Index","url":"https://en.wikipedia.org/wiki/Korea_Citation_Index"}]
검색 결과를 정리하면 다음과 같습니다:
## 검색 결과
나라장터 입찰공고의 불편하고 부정확한 검색기능을 대체할 신경망 기반의 정보검색 모델을 도출하는 연구가 KCI에 등재되어 있습니다. 이 연구는 자연어 검색의 BERT를 기반으로 검색결과를 리랭킹함으로써 사용자의 만족도를 향상시키고자 했습니다.
구체적으로:
- 학습용 데이터셋의 양과 유형, 배치크기, 러닝 레이트 등의 하이퍼파라미터 값 변화에 따른 다양한 실험을 통하여 입찰공고 데이터에 적합한 IR모델을 개발했습니다
- 개발된 IR모델로 실제 입찰공고 조회시 현행 나라장터보다는 훨씬 정확한 검색결과를 보여주었습니다
또한 실무 차원에서 나라장터의 입찰정보뿐 아니라 다른 웹사이트도 크롤링·감시·알림 구현이 가능하며, 특정 조건을 설정하여 어떤 웹 데이터든 자동으로 수집하고 알림받을 수 있습니다.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [CMD] cd "C:/Users/encep/.claude/projects/D--workspace-DMF-Crawler/c00474d0-f118-4917-817d-1c16591aefc7/tool-results" && PYTHONIOENCODING=utf-8 python - <<'EOF'
from pypdf import PdfReader
for f,n in [("webfetch-1788353874771-5fu2oa.pdf",2),("webfetch-1788353877548-psyt0q.pdf",2),("webfetch-1788353892760-
…[truncated 184 chars]
```
===== webfetch-1788353874771-5fu2oa.pdf 26 pages
September 26, 2001 SRCResearch Report 173 High-PerformanceWeb Crawling Marc Najork Allan Heydon Systems Research Center 130 Lytton AvenuePalo Alto, California 94301 http://www.research.compaq.com/SRC/Compaq Systems Research Center SRC’scharter is toadvance the state ofthe art in computer systems by doing basic andappliedresearchinsupportofourcompany’sbusinessobjectives. Ourinterestsand projects span scalable systems (including hardware, networking, distributedsystems, andprogramming-language technology), the Internet (including theWeb,e-commerce, and information retrieval), and human/computer interaction (includ-inguser-interface technology, computer-based appliances, andmobilecomputing).SRCwas established in 1984 by Digital Equipment Corporation. We test the value of our ideas by building hardware and software prototypes and assessing their utility in realistic settings. Interesting systems are too complexto be evaluated solely in the abstract; practical use enables us to investigate theirproperties in depth. This experience is useful in the short term in refining ourdesigns and invaluable in the long term in advancing our knowledge. Most of themajoradvancesininformationsystemshavecomethroughthisapproach,includingpersonal computing, distributed systems, and the Internet. We also perform complementary work of amore mathematical character. Someof that lies in established fields of theoretical computer science, such as the analysisof algorithms, computer-aided geometric design, security and cryptography, andformal specification and verification. Other work explores new ground motivated by problems that arise in our systems research. Wearestrongly committed tocommunicating ourresults; exposing andtesting our ideas inthe research and development communities leads toimproved understand-ing. Our research report series supplements publication in professional journalsand conferences, whileour technical note series allows timelydissemination ofre-cent research findings. We seek users for our prototype systems among those withwhom we have common interests, and we encourage collaboration with universityresearchers.
===== webfetch-1788353877548-psyt0q.pdf 9 pages
Detecting Near -Duplicates forWebCrawling Gurmeet Singh Manku Google Inc. manku@google .comArvind Jain Google Inc. arvind@google .comAnish Das Sarma Stanf ordUniv ersity anishds@stanf ord.edu ABSTRA CT Near-duplicate webdocumen tsareabundan t.Twosuch documen tsdi er fromeachother inaverysmall portion thatdispla ysadvertisemen ts,forexample. Suchdi erences areirrelev antforwebsearch.Sothequalit yofawebcrawler increases ifitcanassess whether anewly crawledwebpage isanear-duplicate ofapreviously crawledwebpageornot. Inthecourse ofdeveloping anear-duplicate detection sys- temforamulti-billion pagerepository ,wemaketworesearc h contributions. First, wedemonstrate thatCharik ar's nger- printingtechnique isappropriate forthisgoal. Second, we presen tanalgorithmic technique foridentifying existing f- bit ngerprin tsthatdi er fromagiven ngerprin tinatmost kbit-positions, forsmall k.Ourtechnique isuseful forboth online queries (single ngerprin ts)andbatchqueries (mul- tiple ngerprin ts).Experimen talevaluation overrealdata con rms thepracticalit yofourdesign. Categories andSubject Descriptors E.1[DataStructures ]:Distributed datastructures; G.2.0 [Discrete Mathematics ]:General; H.3.3 [Information SearchandRetriev al]:Searchprocess General Terms Algorithms Keywords Hamming distance, near-duplicate, similarit y,search,sketch, ngerprin t,webcrawl,webdocumen t 1.INTR ODUCTION Webcrawling isanintegral piece ofinfrastructure for searchengines. Generic crawlers [1,9]crawldocumen ts andlinksbelonging toavarietyoftopics, whereas focused crawlers [27,43,46]usesome specialized knowledge tolimit thecrawltopages pertaining tospeci c topics. Forweb crawling, issues likefreshness andecien tresource usage havepreviously beenaddressed [15,16,19].However,
…[truncated 5289 chars]
```
## [FETCH #43] https://arxiv.org/abs/1405.0749
**ASK:** Give title, authors, year, abstract. Summarize what it says about Mercator, Heritrix, incremental crawlers (Cho & Garcia-Molina), and politeness.
# Paper Summary
**Title:** A Brief History of Web Crawlers
**Authors:** Seyed M. Mirtaheri, Mustafa Emre Dinçktürk, Salman Hooshmand, Gregor V. Bochmann, Guy-Vincent Jourdan, Iosif Viorel Onut
**Year:** 2014
**Abstract:** The paper surveys web crawling techniques from early days through recent developments. It discusses how crawlers evolved from collecting web statistics to performing accessibility and vulnerability checks, while addressing challenges posed by web complexity and expansion.
## Limitations
I cannot provide information about the paper's coverage of Mercator, Heritrix, incremental crawlers (Cho & Garcia-Molina), or politeness strategies based on the webpage content provided.
The page displays only the metadata and abstract, which doesn't contain those specific technical details. The abstract mentions the paper "introduce[s] criteria to evaluate the relative performance of web crawlers" and covers "different technique and algorithms," but specifics about individual crawler systems and techniques aren't included in this excerpt.
To address your questions, you would need access to the full PDF or HTML version of the paper.
## [FETCH #44] https://en.wikipedia.org/wiki/Web_crawler
**ASK:** Summarize the "Re-visit policy" section: freshness and age definitions, Cho and Garcia-Molina uniform vs proportional policy result (uniform better), Poisson change model, Coffman et al. Also the "Politeness policy" section: crawl-delay values used (Mercator 10 seconds, Dill 15 seconds, Cho 10 seconds, Heritrix?). And the "Crawler identification" section. Cite paper references given.
# Web Crawler Policies Summary
## Re-visit Policy
**Freshness and Age Metrics:**
Freshness is a binary measure indicating if a local copy is current (1) or outdated (0). Age measures how long outdated copies remain, calculated as the time elapsed since modification.
**Uniform vs. Proportional Approach:**
Cho and Garcia-Molina demonstrated that "uniform policy outperforms the proportional policy in terms of average freshness" [34]. Counterintuitively, revisiting all pages equally yields better results than prioritizing frequently-changing pages, since rapidly-updated content loses freshness quickly regardless.
**Optimal Strategy:**
"The optimal is closer to the uniform policy than to the proportional policy" [33], with Coffman et al. noting that "accesses to any particular page should be kept as evenly spaced as possible" [33]. The exponential distribution effectively models page changes [35].
## Politeness Policy
**Recommended Intervals:**
Various crawlers employ different delay strategies. The MercatorWeb crawler uses adaptive timing: waiting 10 times the download duration before next access [41]. Cho uses 10-second intervals [34], while WIRE uses 15 seconds as default [40]. Individual access intervals reportedly vary between 20 seconds and 3–4 minutes [43].
**Standard Protocol:**
The robots.txt protocol allows administrators to specify "Crawl-delay:" parameters indicating request intervals [38].
## Crawler Identification
Web crawlers identify themselves via HTTP User-Agent fields, enabling administrators to track visits and contact operators if needed (e.g., accidental spider traps or overload situations).
## [FETCH #45] https://www.emerald.com/ftinr/article-abstract/4/3/175/1328663/Web-Crawling?redirectedFrom=PDF
**ASK:** Give title, authors, year, volume, issue, pages, DOI, and full abstract.
# Web Crawling Article Details
**Title:** Web Crawling
**Authors:** Christopher Olston (Yahoo! Research) and Marc Najork (Microsoft Research)
**Year:** 2010
**Volume:** 4
**Issue:** 3
**Pages:** 175–246
**DOI:** https://doi.org/10.1561/1500000017
**Abstract:**
This is a survey examining the science and practice of web crawling. Though web crawling might initially seem like a straightforward application of breadth-first-search, the field actually presents numerous challenges. These range from systems-level concerns like managing extremely large data structures to theoretical questions such as determining optimal revisit frequencies for dynamic content. The survey identifies fundamental challenges, describes current state-of-the-art models and solutions, and identifies promising directions for future investigation.
## [FETCH #46] https://heritrix.readthedocs.io/en/latest/configuring-jobs.html
**ASK:** Summarize politeness-related settings: delayFactor, minDelayMs, maxDelayMs, maxPerHostBandwidthUsageKbSec, robots policy (obey/ignore), user-agent requirement with contact URL, and crawl scope/frontier settings. Quote exact property names.
# Heritrix Politeness Configuration Summary
## Key Politeness Settings
**Delay Controls:**
- `delayFactor`: "a multiple of the amount of time it took to fetch the last URI" (default 5.0)
- `minDelayMs`: enforces minimum wait between requests, "takes precedence over the value calculated by delayFactor"
- `maxDelayMs`: upper bound on politeness delays (default 30000ms)
**Bandwidth Management:**
- `maxPerHostBandwidthUsageKbSec`: "limits the maximum bandwidth to use for any host"
**Robots.txt Compliance:**
- `robotsPolicyName` options: "obey" (default), "classic", "robotsTxtOnly", or "ignore"
- The system supports RFC 9309 path wildcards in robots.txt rules
**Operator Identification:**
- `metadata.operatorContactUrl`: "gives the administrator of a crawled host a URI to refer to in case of problems"
- User-Agent should include valid contact information
**Frontier/Scope Controls:**
- `maxToeThreads`: "maximum number of toe threads to run" (recommended ~2x host count for domain crawls)
- `extract404s`: determines whether links are extracted from 404 responses
- Rules-based scope limiting via DecideRules framework
These settings work collectively to ensure crawlers respect server resources and administrator policies.
## [FETCH #47] https://homes.cs.washington.edu/~weld/pubs.html
**ASK:** Find the entry for "Wrapper Induction for Information Extraction" (Kushmerick, Weld, Doorenbos) and give its venue and year. Also any "Wrapper induction" journal version (Artificial Intelligence 2000?).
# Wrapper Induction for Information Extraction
Based on the content provided, I found the following entries:
**Conference Paper:**
"N. Kushmerick and R. Doorenbos and D. Weld 'Wrapper Induction for Information Extraction' (IJCAI-97, August 1997)"
The venue was the International Joint Conference on Artificial Intelligence (IJCAI), held in August 1997.
**Journal Version:**
I did not locate a journal version in an Artificial Intelligence journal from 2000 or any other year in the provided content. The only wrapper induction entry listed is the IJCAI-97 conference paper.
## [FETCH #48] https://cdn.aaai.org/AAAI/1999/AAAI99-011.pdf
**ASK:** Give title, author, venue, year. Summarize the RAPTURE wrapper verification algorithm: features (word count, average word length, density of numeric chars etc), Gaussian model per feature, combining probabilities, results.
I apologize, but the content provided appears to be a binary PDF file encoded in a format I cannot reliably parse. The raw PDF stream data doesn't contain readable text that would allow me to extract:
- Title, author, and venue information
- Details about the RAPTURE wrapper verification algorithm
- Specific features, model parameters, or results
To help you effectively, I would need:
1. A text-based version of the document, or
2. A properly decoded PDF with accessible text content
If you have access to the original PDF file, you could try:
- Converting it to plain text using a PDF reader or OCR tool
- Copying and pasting the relevant sections directly
- Providing a DOI or document link for reference
Once you provide readable source material, I'll be happy to summarize the RAPTURE algorithm details within your specified parameters.
[Binary content (application/pdf, 591.6KB) also saved to C:\Users\encep\.claude\projects\D--workspace-DMF-Crawler\c00474d0-f118-4917-817d-1c16591aefc7\tool-results\webfetch-1788354016451-x0j250.pdf]
## [FETCH #49] https://portal.fis.tum.de/en/publications/robula-an-algorithm-for-generating-robust-xpath-locators-for-web-
**ASK:** Give title, authors, journal, year, volume, issue, pages, DOI, and abstract of Robula+.
# Robula+: Publication Details
**Title:** Robula+: An algorithm for generating robust XPath locators for web testing
**Authors:** Maurizio Leotta, Andrea Stocco, Filippo Ricca, Paolo Tonella
**Journal:** Journal of Software: Evolution and Process
**Year:** 2016
**Volume:** 28
**Issue:** 3
**Pages:** 177-204
**DOI:** https://doi.org/10.1002/smr.1771
**Abstract:**
The paper addresses test code fragility in automated web testing. When applications evolve, element locators in test scripts often break, requiring manual repair. The authors propose Robula+, an algorithm that generates resilient XPath-based locators designed to survive application changes. Comparative testing against competing tools demonstrated significant improvements: "Robula+ reduces the locators' fragility on average by 90% w.r.t. absolute locators and by 63% w.r.t. Selenium IDE locators."
## [FETCH #50] https://link.springer.com/article/10.1007/s44443-025-00071-w
**ASK:** Give title, authors, journal, year, DOI, abstract. Explain how LLMs generate XPath from seed pages, the multi-task decomposition, and results (accuracy, number of LLM calls).
REDIRECT DETECTED: The URL redirects to a location that was not fetched automatically.
Original URL: https://link.springer.com/article/10.1007/s44443-025-00071-w
Redirect URL (from the server's Location header — server-supplied, not verified): https://idp.springer.com/authorize?response_type=cookie&client_id=springerlink&redirect_uri=https%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs44443-025-00071-w
Status: 303 See Other
To complete your request, I need to fetch content from the redirected URL. Please use WebFetch again with these parameters:
- url: "https://idp.springer.com/authorize?response_type=cookie&client_id=springerlink&redirect_uri=https%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs44443-025-00071-w"
- prompt: "Give title, authors, journal, year, DOI, abstract. Explain how LLMs generate XPath from seed pages, the multi-task decomposition, and results (accuracy, number of LLM calls)."
## [FETCH #51] https://en.wikipedia.org/wiki/SimHash
**ASK:** Summarize: who invented SimHash (Charikar 2002, venue), how Google used it (Manku et al. 2007 WWW), and how the algorithm works (feature hashing, weighted bit sums, sign -> bits; Hamming distance).
# SimHash: Invention, Application, and Mechanism
**Inventor and Origins**
Moses Charikar created SimHash, publishing "Similarity estimation techniques from rounding algorithms" at the 2002 ACM Symposium on Theory of Computing.
**Google's Implementation**
In 2007, Google researchers Manku, Jain, and Das Sarma documented using SimHash for identifying near-duplicate web pages during crawling, as detailed in their paper presented at the International Conference on World Wide Web.
**Algorithm Mechanics**
SimHash operates through several steps: Input data is decomposed into distinct features, each feature receives its own hash value, then a composite hash emerges by analyzing bit positions across all feature hashes. For each bit position, the algorithm counts instances where the bit equals 1 versus 0; if ones dominate, that position in the final hash becomes 1, otherwise 0.
The resulting hashes maintain a crucial property: similar input datasets produce hashes with minimal bitwise Hamming distance differences. This enables efficient duplicate detection by comparing hash values rather than entire documents, and allows discovery of similar content through simple sorting rather than exhaustive O(n²) comparisons.
## [FETCH #52] https://en.wikipedia.org/wiki/MinHash
**ASK:** Summarize: who invented MinHash (Broder 1997, venue), Jaccard similarity estimation, min-wise independent permutations, use in AltaVista duplicate detection, and LSH banding.
# MinHash: Key Innovations and Applications
**Inventor & Publication:** Andrei Broder published MinHash in a 1997 conference proceeding, introducing this technique for rapidly evaluating set similarity.
**Jaccard Similarity Estimation:** MinHash estimates the Jaccard index without explicitly computing intersection and union. The core insight is that "the probability that hmin(A) = hmin(B) is true is equal to the similarity J(A,B)," allowing efficient similarity approximation through hash-based sampling.
**Min-wise Independent Permutations:** The scheme relies on random permutations where any element is equally likely to be the minimum across subsets. However, truly random permutations require prohibitively large storage. Researchers developed practical approximations: restricted min-wise independence (limited to small sets) and approximate min-wise independence (allowing fixed error probability ε).
**AltaVista Application:** MinHash was "initially used in the AltaVista search engine to detect duplicate web pages and eliminate them from search results," demonstrating its practical value in web-scale deduplication.
**LSH Connection:** MinHash functions as a locality-sensitive hashing scheme, mapping similar sets to identical hash signatures. This enables faster nearest-neighbor searches and clustering without comparing full set contents directly.
## [SEARCH #27] 의약품안전나라 크롤링 논문 KCI 의약품 허가 데이터 자동 수집 파이썬 Selenium 연구
Web search results for query: "의약품안전나라 크롤링 논문 KCI 의약품 허가 데이터 자동 수집 파이썬 Selenium 연구"
Web search was not performed: this session has used its web search budget (200 of 200 WebSearch calls). Continue with the information already gathered instead of issuing more searches. If more searches are genuinely needed, ask the user to raise CLAUDE_CODE_MAX_WEB_SEARCHES_PER_SESSION.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #28] Kimball slowly changing dimension type 2 effective date current flag definition dimensional modeling techniques
Web search results for query: "Kimball slowly changing dimension type 2 effective date current flag definition dimensional modeling techniques"
Web search was not performed: this session has used its web search budget (200 of 200 WebSearch calls). Continue with the information already gathered instead of issuing more searches. If more searches are genuinely needed, ask the user to raise CLAUDE_CODE_MAX_WEB_SEARCHES_PER_SESSION.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [SEARCH #29] Lerman Minton Knoblock "Wrapper maintenance: a machine learning approach" JAIR 2003 wrapper verification reinduction
Web search results for query: "Lerman Minton Knoblock "Wrapper maintenance: a machine learning approach" JAIR 2003 wrapper verification reinduction"
Web search was not performed: this session has used its web search budget (200 of 200 WebSearch calls). Continue with the information already gathered instead of issuing more searches. If more searches are genuinely needed, ask the user to raise CLAUDE_CODE_MAX_WEB_SEARCHES_PER_SESSION.
REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.
## [FETCH #53] https://docs.scrapy.org/en/latest/topics/autothrottle.html
**ASK:** Summarize AutoThrottle settings: AUTOTHROTTLE_ENABLED, AUTOTHROTTLE_START_DELAY, AUTOTHROTTLE_MAX_DELAY, AUTOTHROTTLE_TARGET_CONCURRENCY, DOWNLOAD_DELAY, and the throttling algorithm. Also mention ROBOTSTXT_OBEY if present.
# AutoThrottle Settings Summary
**AUTOTHROTTLE_ENABLED** (Default: `False`): Activates the AutoThrottle extension for dynamic throttling.
**AUTOTHROTTLE_START_DELAY** (Default: `5.0`): Sets the initial download delay in seconds when crawling begins.
**AUTOTHROTTLE_MAX_DELAY** (Default: `60.0`): Establishes the ceiling for download delays during high-latency situations.
**AUTOTHROTTLE_TARGET_CONCURRENCY** (Default: `1.0`): Specifies the average parallel requests per remote site. "A lower value makes the crawler more conservative and polite."
**DOWNLOAD_DELAY**: The minimum allowable delay; AutoThrottle respects this floor value and won't decrease delays below it.
## Throttling Algorithm
The extension operates through these steps:
1. Spiders commence with the configured start delay
2. Upon receiving responses, target delay equals `latency / N` (where N is target concurrency)
3. The next request delay becomes the average of the previous and target delays
4. Non-200 responses can only increase delays, never decrease them
5. Final delay remains bounded between DOWNLOAD_DELAY minimum and AUTOTHROTTLE_MAX_DELAY maximum
**Note**: ROBOTSTXT_OBEY is not mentioned in the provided content.
## [FETCH #54] https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002883147
**ASK:** 논문 제목, 저자, 학술지명, 발행연도, 권호, 초록을 알려줘. 입찰공고 데이터 수집(크롤링) 방식과 검색 모델 구조를 요약해줘.
# 논문 정보
**제목:** 나라장터 입찰공고 인공지능 검색모델 개발에 관한 연구
**저자:** 이선표, 현철호, 장수현, 지학수, 박승범
**학술지:** 정보화연구 (The Journal of Information Technology and Architecture)
**발행연도:** 2022
**권호:** 19권 3호
**초록 요약:** "나라장터의 검색 기능은 매우 부정확하여 많은 사용자들이 불편을 느끼고 있다." 이를 개선하기 위해 신경망 기반 정보검색 모델을 개발했습니다.
---
# 데이터 수집 및 검색 모델 구조
**데이터 수집 방식:**
웹 페이지의 구체적인 크롤링 방법은 명시되어 있지 않습니다. 다만 "문서를 구절로 분할하고, 분할된 구절에서 키워드를 추출하여 의사-질의를 생성"하는 전처리 과정이 설명됩니다.
**검색 모델 구조:**
1. **초기 검색:** Elastic Search의 BM25 모델 활용
2. **재순위화:** BERT 기반 신경망으로 검색결과 재정렬
3. **학습 데이터:** 의사-질의와 의사-레이블(질의-문서 쌍)을 생성하여 약지도학습 방식 적용
## [CMD] cd "C:/Users/encep/.claude/projects/D--workspace-DMF-Crawler/c00474d0-f118-4917-817d-1c16591aefc7/tool-results" && PYTHONIOENCODING=utf-8 python - <<'EOF'
from pypdf import PdfReader
import re
def dump(f, pages, maxc=4000, grep=None):
r=PdfReader(f)
txt="\n".join((r.pages[i].extract_text() o
…[truncated 756 chars]
```
<persisted-output>
Output too large (52.4KB). Full output saved to: C:\Users\encep\.claude\projects\D--workspace-DMF-Crawler\c00474d0-f118-4917-817d-1c16591aefc7\tool-results\bpwb3m0gh.txt
Preview (first 2KB):
===== webfetch-1788354016451-x0j250.pdf pages [0, 1] total 6
Regression testing for wrapper maintenance Nicholas Kushmerick Department of Computer Science, University College Dublin, Dublin 4, Ireland nick@ucd.ie Abstract Recent work on Internet information integration ~- sumes a library of wrappers, specialized information ex- traction procedures. Maintaining wrappers is difficult, because the formatting regularities on which they rely often change. The wrapper verification problem is to determine whether a wrapper is correct. Standard re- gression testing approaches are inappropriate, because both the formatting regularities and a site’s underly- ing content may change. We introduce RAPTURE, a fully-implemented, domain-independent verification al- gorithm. RAPTURE uses well-motivated heuristics to compute the similarity between a wrapper’s expected and observed output. Experiments with 27 actual In- ternet sites show a substantial performance improve- ment over standard regression testing. Introduction Systems that integrate heterogeneous information sources have recently received substantial research at- tention (e.g. (Wiederhold 1996; Knoblock et al. 1998; Levy et al. 1998)). A ’movie information’ integrator, for example, might provide a single interface to the re- view, cast list, and schedule information available from dozens of Internet sites. Such systems rely on a library of wrappers, specialized procedures for extracting the content from a particular site. For example, the site in Fig. 1 lists countries and their telephone country codes. The information extrac- tion task is to identify the (county, code) pairs in this site’s pages. The ccwrap wrapper does so by scanning for the delimiters <B>...</B> and <I>...</I>, which works because of a formatting regularity: countries are bold and codes are italic. Scalability is the main challenge to building wrap- pers. While they are usually rather short programs, writing wrappers by hand is tedious and error-prone
...
</persisted-output>
```
## [FETCH #55] https://api.semanticscholar.org/graph/v1/paper/DOI:10.1145/958942.958945?fields=title,authors,year,venue,abstract,citationCount
**ASK:** Return the JSON fields: title, authors, year, venue, abstract, citationCount.
```json
{
"title": "Effective page refresh policies for Web crawlers",
"authors": [
"Junghoo Cho",
"H. Garcia-Molina"
],
"year": 2003,
"venue": "TODS",
"abstract": null,
"citationCount": 314
}
```
**Note:** The abstract field is unavailable in the provided data. The publisher has elided this information, though it may be accessible through the DOI link referenced in the open access status.
## [FETCH #56] https://idp.springer.com/authorize?response_type=cookie&client_id=springerlink&redirect_uri=https%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs44443-025-00071-w
**ASK:** Give title, authors, journal, year, DOI, abstract. Explain how LLMs generate XPath from seed pages, the multi-task decomposition, and results (accuracy, number of LLM calls).
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Redirect URL (from the server's Location header — server-supplied, not verified): https://link.springer.com/article/10.1007/s44443-025-00071-w?error=cookies_not_supported&code=52df85a8-32c8-4d47-beaf-5cbd0fa0a5fe
Status: 302 Found
To complete your request, I need to fetch content from the redirected URL. Please use WebFetch again with these parameters:
- url: "https://link.springer.com/article/10.1007/s44443-025-00071-w?error=cookies_not_supported&code=52df85a8-32c8-4d47-beaf-5cbd0fa0a5fe"
- prompt: "Give title, authors, journal, year, DOI, abstract. Explain how LLMs generate XPath from seed pages, the multi-task decomposition, and results (accuracy, number of LLM calls)."
## [FETCH #57] https://arxiv.org/abs/1106.4872
**ASK:** Give title, authors, venue (JAIR vol/year), abstract. Summarize wrapper verification (detect when wrapper breaks using statistical features of extracted data) and wrapper reinduction.
# Wrapper Maintenance: A Machine Learning Approach
**Authors:** C. A. Knoblock, K. Lerman, S. N. Minton
**Venue:** Journal of Artificial Intelligence Research, Volume 18, pages 149-181, 2003
## Abstract
The paper addresses the challenge of maintaining web data extraction wrappers as online sources evolve. The authors present "an efficient algorithm that learns structural information about data from positive examples alone," enabling two key applications: wrapper verification and reinduction.
## Wrapper Verification
This component detects when wrappers fail due to web source format changes. The system analyzes statistical features of extracted data to identify breakage. Testing on 27 wrappers over one year achieved precision of 0.73 and recall of 0.95, correctly discovering 35 of 37 wrapper failures.
## Wrapper Reinduction
When wrappers break, this algorithm automatically recovers by identifying data patterns on modified web pages to generate updated extractors. Validation across ten sources demonstrated precision and recall values of 0.90 and 0.80 respectively on data extraction tasks.
The research demonstrates that machine learning can effectively automate wrapper maintenance, addressing a previously under-researched but practically important problem in web data extraction.
## [FETCH #58] https://api.semanticscholar.org/graph/v1/paper/search?query=Introduction+to+Heritrix+Mohr+Stack+Ranitovic+Avery+Kimpton&fields=title,authors,year,venue,citationCount&limit=3
**ASK:** Return the JSON results: for each paper title, authors, year, venue, citationCount.
The server returned HTTP 429 Too Many Requests.
The response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.
## [FETCH #59] https://dl.acm.org/doi/10.1145/958942.958945
**ASK:** Give title, authors, journal, volume, issue, year, pages, abstract.
The server returned HTTP 403 Forbidden.
The response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.
## [FETCH #60] https://www.kimballgroup.com/data-warehouse-business-intelligence-resources/kimball-techniques/dimensional-modeling-techniques/type-2/
**ASK:** Summarize the Type 2 Slowly Changing Dimension technique: add new row, effective/expiration dates, current row indicator.
# Type 2 Slowly Changing Dimension Summary
**Core Concept:**
Type 2 SCD handles dimension changes by introducing new rows rather than updating existing ones. As the source explains, "a new row in the dimension with the updated attribute values" captures each change state.
**Key Implementation Requirements:**
1. **Surrogate Key Strategy**: Since multiple rows now represent a single member, the dimension must use a surrogate key as its primary key instead of the natural/durable key.
2. **Three Essential Columns**:
- **Effective Date**: Marks when the change took effect
- **Expiration Date**: Indicates when the row became obsolete
- **Current Row Indicator**: A flag identifying the active dimension record
**How It Works:**
When an attribute changes, a fresh dimension row receives a new surrogate key, which becomes the foreign key in all subsequent fact table records until another change occurs. This creates a complete historical audit trail while maintaining referential integrity across fact tables.
This approach preserves dimensional history for time-based analytics while keeping the data model simple and maintainable.
## [FETCH #61] https://osu-nlp-group.github.io/Mind2Web/
**ASK:** Summarize the MindAct framework: small LM candidate generation over DOM elements, LLM multiple-choice action prediction, and reported results on cross-task/cross-website/cross-domain splits.
# MindAct Framework Summary
Based on the provided content, I cannot find detailed information about the MindAct framework's specific architecture or reported results. The webpage mentions that "fine-tuning code/models for MindAct" were updated to the GitHub repository (as of August 2023), but the document doesn't elaborate on the framework's components or performance metrics.
The only relevant framework description states: "While the raw HTML of real-world websites are often too large to be fed to LLMs, we show that first filtering it with a small LM significantly improves the effectiveness and efficiency of LLMs."
This suggests a two-stage approach using a smaller language model for filtering before LLM processing, but the webpage lacks specifics about:
- How candidate generation works over DOM elements
- The multiple-choice action prediction mechanism
- Quantitative results on cross-task, cross-website, and cross-domain generalization splits
For comprehensive MindAct details, you would need to consult the arXiv paper (2306.06070) or the GitHub repository directly.
## [FETCH #62] https://github.com/scrapinghub/python-simhash
**ASK:** Summarize README: what the library does, language, API usage example, license, and stars if shown.
# python-simhash Summary
**What it does:** An efficient implementation of simhash functions for near-duplicate detection in web crawling and data processing, based on Charikar's simhash algorithm.
**Language:** Python with C extensions and GCC.
**Key functions:**
- `fingerprint()` - generates fingerprints from hash sequences
- `hamming_distance()` - measures bit differences between hashes
- `simpair_indices()` - finds similar hashes within a threshold
- `fnvhash()` - FNV-1a hash generation
**API Example:**
```python
from simhash import fingerprint, hamming_distance
hash1 = fingerprint(map(hash, "some text we want to hash"))
hash2 = fingerprint(map(hash, "some more text we want to hash"))
hamming_distance(hash1, hash2) # Returns: 2
```
**License:** BSD-3-Clause
**Community:** 127 stars, 11 watchers, 29 forks (archived June 24, 2026)
## [FETCH #63] https://api.semanticscholar.org/graph/v1/paper/search?query=The+Evolution+of+the+Web+and+Implications+for+an+Incremental+Crawler&fields=title,authors,year,venue,abstract,citationCount&limit=2
**ASK:** Return the JSON results: for each paper title, authors, year, venue, abstract, citationCount.
The server returned HTTP 429 Too Many Requests.
The response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.
## [FETCH #64] https://api.semanticscholar.org/graph/v1/paper/search?query=Introduction+to+Heritrix+archival+quality+web+crawler&fields=title,authors,year,venue,citationCount&limit=3
**ASK:** Return the JSON results: for each paper title, authors, year, venue, citationCount.
The server returned HTTP 429 Too Many Requests.
The response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.
## [FETCH #65] https://link.springer.com/article/10.1007/s44443-025-00071-w?error=cookies_not_supported&code=52df85a8-32c8-4d47-beaf-5cbd0fa0a5fe
**ASK:** Give title, authors, journal, year, DOI, abstract. Explain how LLMs generate XPath from seed pages, the multi-task decomposition, and results (accuracy, number of LLM calls).
# Article Summary
**Title:** Automatic XPath generation agents for vertical websites by LLMs
**Authors:** Jing Huang, Jie Song
**Journal:** Journal of King Saud University Computer and Information Sciences
**Year:** 2025
**DOI:** 10.1007/s44443-025-00071-w
## Abstract
The researchers present a framework addressing structured data extraction from domain-specific websites through LLM-generated XPath expressions. The system reduces reliance on expensive repeated LLM calls while maintaining high accuracy for information retrieval from similar web pages.
## How LLMs Generate XPath from Seed Pages
The framework uses a three-stage decomposition strategy:
1. **Attribute Extraction:** LLMs extract target information from 2-3 seed pages, converting HTML to Markdown first to improve comprehension.
2. **Target Node Localization:** The system identifies candidate DOM nodes containing extracted text, then uses "perturbation testing"—modifying text in each node to see which changes affect the LLM's output. Correct nodes are those whose modification alters extraction results.
3. **XPath Generation:** Rather than absolute paths vulnerable to structural changes, the framework uses "anchor nodes" (distinctive nearby elements) to generate relative XPaths with superior robustness.
## Key Results
- **Accuracy:** Achieves F1 scores of 86.83-92.46, surpassing comparison methods by 14.84-23.86 percentage points
- **LLM Efficiency:** Requires only n_s (seed pages) + p·n_s + 1 calls versus n calls for direct extraction, yielding substantial savings for sites with >10 pages
- **Model Requirements:** Works effectively with smaller 8×7B models, not requiring large proprietary LLMs
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