Article

A framework for web table mining

Authors:

Yingchen Yang,

Wo-Shun LukAuthors Info & Claims

WIDM '02: Proceedings of the 4th international workshop on Web information and data management

Pages 36 - 42

https://doi.org/10.1145/584931.584940

Published: 08 November 2002 Publication History

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Abstract

Web table mining is about information extraction from tables published inside web pages as HTML texts. Most previous work on this subject makes use of the tags to discover components of the table. Our work treats web as a distinct publication media, in two ways. We argue that new types of table format have been developed specially for the web. We also argue that the visual cues embedded within the HTML text, are utilized by the authors to direct the viewer on how to read the contents contained a web table properly. We develop a framework for comprehensively analyzing the structural aspects of a web table, within which rules are devised to process and extract attribute-value pairs from the table. This approach to web table mining is validated by good experimental results.

References

[1]

H. Chen, S. Tsai, and J. Tasi, Ming Tables from Large Scale HTML Texts, In Proc. 18th International Conference on Computational Linguistics, Saabrucken, Germany, July 2000]]

Digital Library

Google Scholar

[2]

M. Hurst, Classifying TABLE Elements in HTML. In Poster, 11th International World Wide Web Conference, Honolulu, HI, May 2002, http://www2002.org/CDROM/poster/115/index.html]]

Google Scholar

[3]

H. Ng, C. Lim, and J. Koo, Learning to Recognize Tables in Free Text, In Proc. of the 37th Annual Meeting of ACL, 1999, p. 443--450.]]

Digital Library

Google Scholar

[4]

Y. Wang, and J. Hu, A Machine Learning Based Approach for Table Detection on The Web, In Proc. 11th International World Wide Web Conference, Honolulu, HI, May 2002, pp. 242--250]]

Digital Library

Google Scholar

[5]

X. Wang, and D. Wood, A Conceptual Model for Tables, In Proc. of Principles of Digital Document Processing, 4th International Workshop, PODDP'98, Saint Malo, France, March, 1998, Lecture Notes in Computer Science, Vol. 1481]]

Digital Library

Google Scholar

[6]

Y. Yang, Web Table Mining and Database Discovery, M.Sc. thesis, Simon Fraser University, August, 2002]]

Google Scholar

[7]

M. Yoshida, K. Torisawa, and J. Tsujji, A Method to Integrate Tables of the World Wide Web, In Proc. 1st International Workshop on Web Document Analysis, Seattle, WA, USA, September 2001, pp. 31--34]]

Google Scholar

Cited By

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Haider WYesilada Y(2022)Classification of Layout vs. Relational Tables on the Web: Machine Learning with Rendered PagesACM Transactions on the Web10.1145/355534917:1(1-23)Online publication date: 20-Dec-2022
https://dl.acm.org/doi/10.1145/3555349
Roldán JJiménez PCorchuelo R(2022)On extracting data from tables that are encoded using HTMLKnowledge-Based Systems10.1016/j.knosys.2019.105157190:COnline publication date: 22-Apr-2022
https://dl.acm.org/doi/10.1016/j.knosys.2019.105157
Roldán JJiménez PSzekely PCorchuelo R(2022)TOMATEInformation Sciences: an International Journal10.1016/j.ins.2021.04.087577:C(49-68)Online publication date: 22-Apr-2022
https://dl.acm.org/doi/10.1016/j.ins.2021.04.087
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Index Terms

A framework for web table mining
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Document filtering
      2. Information extraction

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Published In

WIDM '02: Proceedings of the 4th international workshop on Web information and data management

November 2002

116 pages

ISBN:1581135939

DOI:10.1145/584931

Program Chairs:
Roger Chiang
University of Cincinnati, USA
,
Ee-Peng Lim
Chinese University of Hong Kong, Hong Kong, China

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 November 2002

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CIKM02

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CIKM02: Eleventh ACM International Conference on Information and Knowledge Management

November 8, 2002

Virginia, McLean, USA

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Cited By

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Haider WYesilada Y(2022)Classification of Layout vs. Relational Tables on the Web: Machine Learning with Rendered PagesACM Transactions on the Web10.1145/355534917:1(1-23)Online publication date: 20-Dec-2022
https://dl.acm.org/doi/10.1145/3555349
Roldán JJiménez PCorchuelo R(2022)On extracting data from tables that are encoded using HTMLKnowledge-Based Systems10.1016/j.knosys.2019.105157190:COnline publication date: 22-Apr-2022
https://dl.acm.org/doi/10.1016/j.knosys.2019.105157
Roldán JJiménez PSzekely PCorchuelo R(2022)TOMATEInformation Sciences: an International Journal10.1016/j.ins.2021.04.087577:C(49-68)Online publication date: 22-Apr-2022
https://dl.acm.org/doi/10.1016/j.ins.2021.04.087
Jiménez PRoldán JCorchuelo R(2022)A coral-reef approach to extract information from HTML tablesApplied Soft Computing10.1016/j.asoc.2021.107980115:COnline publication date: 6-May-2022
https://dl.acm.org/doi/10.1016/j.asoc.2021.107980
Jiménez PRoldán JCorchuelo R(2022)A hybrid quantum approach to leveraging data from HTML tablesKnowledge and Information Systems10.1007/s10115-021-01636-7Online publication date: 8-Jan-2022
https://doi.org/10.1007/s10115-021-01636-7
Shigarov A(2022)Table understanding: Problem overviewWIREs Data Mining and Knowledge Discovery10.1002/widm.148213:1Online publication date: 21-Nov-2022
https://doi.org/10.1002/widm.1482
Jiménez PRoldán JCorchuelo R(2021)A clustering approach to extract data from HTML tablesInformation Processing and Management: an International Journal10.1016/j.ipm.2021.10268358:6Online publication date: 1-Nov-2021
https://dl.acm.org/doi/10.1016/j.ipm.2021.102683
Nandakwang JChongstitvatana P(2020)TULIP: A Five-Star Table and List - From Machine-Readable to Machine-Understandable SystemsLinked Open Data - Applications, Trends and Future Developments10.5772/intechopen.91406Online publication date: 19-Nov-2020
https://doi.org/10.5772/intechopen.91406
Yu WPeng WShu YZeng QJiang M(2020)Experimental Evidence Extraction System in Data Science with Hybrid Table Features and Ensemble LearningProceedings of The Web Conference 202010.1145/3366423.3380174(951-961)Online publication date: 20-Apr-2020
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Yu WLi ZZeng QJiang M(2019)Tablepedia: Automating PDF Table Reading in an Experimental Evidence Exploration and Analytic SystemThe World Wide Web Conference10.1145/3308558.3314118(3615-3619)Online publication date: 13-May-2019
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