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Record-boundary discovery in Web documents

Published: 01 June 1999 Publication History

Abstract

Extraction of information from unstructured or semistructured Web documents often requires a recognition and delimitation of records. (By “record” we mean a group of information relevant to some entity.) Without first chunking documents that contain multiple records according to record boundaries, extraction of record information will not likely succeed. In this paper we describe a heuristic approach to discovering record boundaries in Web documents. In our approach, we capture the structure of a document as a tree of nested HTML tags, locate the subtree containing the records of interest, identify candidate separator tags within the subtree using five independent heuristics, and select a consensus separator tag based on a combined heuristic. Our approach is fast (runs linearly for practical cases within the context of the larger data-extraction problem) and accurate (100% in the experiments we conducted).

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  • (2018)Development of Web-based Automated System for Cyber Analytic Applications2018 9th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)10.1109/UEMCON.2018.8796792(866-871)Online publication date: Nov-2018
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cover image ACM Conferences
SIGMOD '99: Proceedings of the 1999 ACM SIGMOD international conference on Management of data
June 1999
604 pages
ISBN:1581130848
DOI:10.1145/304182
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 June 1999

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Overall Acceptance Rate 785 of 4,003 submissions, 20%

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View all
  • (2022)Web Record Extraction with InvariantsProceedings of the VLDB Endowment10.14778/3574245.357427616:4(959-972)Online publication date: 1-Dec-2022
  • (2020)Web Page Segmentation RevisitedProceedings of the 29th ACM International Conference on Information & Knowledge Management10.1145/3340531.3412782(3047-3054)Online publication date: 19-Oct-2020
  • (2018)Development of Web-based Automated System for Cyber Analytic Applications2018 9th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)10.1109/UEMCON.2018.8796792(866-871)Online publication date: Nov-2018
  • (2017)Issues and Challenges in Web Crawling for Information ExtractionBio-Inspired Computing for Information Retrieval Applications10.4018/978-1-5225-2375-8.ch004(93-121)Online publication date: 2017
  • (2016)Practical Web Data Extraction: Are We There Yet? - A Short Survey2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI)10.1109/WI.2016.0096(562-567)Online publication date: Oct-2016
  • (2015)TEGRAProceedings of the 2015 ACM SIGMOD International Conference on Management of Data10.1145/2723372.2723725(1713-1728)Online publication date: 27-May-2015
  • (2014)Bottom-up region extractor for semi-structured web pages2014 International Computer Science and Engineering Conference (ICSEC)10.1109/ICSEC.2014.6978209(284-289)Online publication date: Jul-2014
  • (2013)Robust detection of semi-structured web records using a DOM structure-knowledge-driven modelACM Transactions on the Web10.1145/25084347:4(1-32)Online publication date: 1-Nov-2013
  • (2013)A Survey on Region Extractors from Web DocumentsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2012.13525:9(1960-1981)Online publication date: 1-Sep-2013
  • (2013)LBDA: A novel framework for extracting content from web pages2013 International Conference on Advanced Computing and Communication Systems10.1109/ICACCS.2013.6938748(1-7)Online publication date: Dec-2013
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