Article

IEPAD: information extraction based on pattern discovery

Authors:

Chia-Hui Chang,

Shao-Chen LuiAuthors Info & Claims

WWW '01: Proceedings of the 10th international conference on World Wide Web

Pages 681 - 688

https://doi.org/10.1145/371920.372182

Published: 01 April 2001 Publication History

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[1]

Chang, C.H.; Lui, S.C.; and Wu, Y.C. Applying pattern mining to Web information extraction. In Proceedings of the Fifth Pacific Asia Conference on Knowledge Discovery and Data Mining, Apr. 2001, Hong Kong.]]

Digital Library

Google Scholar

[2]

Chien, L.F. PAT-tree-based keyword extraction for Chinese information retrieval. In Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval. pp. 50-58. 1997.]]

Digital Library

Google Scholar

[3]

Doorenbos, R.B.; Etzioni, O.; and Weld, D. S. A scalable comparison-shopping agent for the World Wide Web. In Proceedings of the first international conference on Autonomous Agents. pp. 39-48, NewYork, NY, 1997, ACM Press.]]

Digital Library

Google Scholar

[4]

Embley, D.; Jiang, Y.; and Ng, Y. -K. 1999. Recordboundary discovery in Web documents. In Proceedings of the 1999 ACM SIGMOD International Conference on Management of Data (SIGMOD'99)}. pp. 467-478, Philadelphia, Pennsylvania.]]

Digital Library

Google Scholar

[5]

Gonnet, G.H.; Baeza-yates, R.A.; and Snider, T. 1992. New Indices for Text: Pat trees and Pat Arrays. Information Retrieval: Data Structures and Algorithms, Prentice Hall.]]

Digital Library

Google Scholar

[6]

Gusfield, D. 1997. Algorithms on strings, tree, and sequence, Cambridge. 1997.]]

Digital Library

Google Scholar

[7]

Hsu, C.-N., and Dung, M.-T. 1998. Generating finite-state transducers for semi-structured data extraction from the Web. Information Systems. 23(8): 521-538.]]

Digital Library

Google Scholar

[8]

Knoblock, A. et al., Eds. 1998. In Proceedings of the 1998 Workshop on AI and Information Integration, Menlo Park, California. AAAI Press.]]

Google Scholar

[9]

Kurtz, S., and Schleiermacher, C. 1999. REPuter: fast computation of maximal repeats in complete genomes. Bioinformatics 15(5): 426-427.]]

Crossref

Google Scholar

[10]

Kushmerick, N. 1999. Gleaning the Web. IEEE Intelligent Systems 14(2): 20-22.]]

Digital Library

Google Scholar

[11]

Kushmerick, N.; Weld, D.; and Doorenbos, R. 1997. Wrapper induction for information extraction. In Proceedings of the 15th International Joint Conference on Artificial Intelligence (IJCAI).]]

Google Scholar

[12]

Morrison, D. R. Journal of ACM, 15, pp. 514-534, 1968.]]

Digital Library

Google Scholar

[13]

Muslea, I.; Minton, S.; and Knoblock, C. 1999. A hierarchical approach to wrapper induction. In Proceedings of the 3rd International Conference on Autonomous Agents (Agents '99), Seattle, WA.]]

Digital Library

Google Scholar

[14]

Muslea, I. 1999. Extraction patterns for information extraction tasks: a survey. In Proceedings of AAAI '99: Workshop on Machine Learning for Information Extraction]]

Google Scholar

[15]

Sedgewick, R. Algorithms in C, Addison Wesley, 1990.]]

Digital Library

Google Scholar

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Nunes MDorneles C(2023)EDREW - Enhanced Data Representation for Extraction in WebProceedings of the 29th Brazilian Symposium on Multimedia and the Web10.1145/3617023.3617055(230-237)Online publication date: 23-Oct-2023
https://dl.acm.org/doi/10.1145/3617023.3617055
Chen ZMeng WDragut E(2022)Web Record Extraction with InvariantsProceedings of the VLDB Endowment10.14778/3574245.357427616:4(959-972)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.14778/3574245.3574276
Kumaresan URamanujam K(2021)A Framework for Automated Scraping of Structured Data Records From the Deep Web Using Semantic LabelingInternational Journal of Information Retrieval Research10.4018/IJIRR.29083012:1(1-18)Online publication date: 4-Nov-2021
https://doi.org/10.4018/IJIRR.290830
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IEPAD: information extraction based on pattern discovery

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WWW '01: Proceedings of the 10th international conference on World Wide Web

May 2001

770 pages

ISBN:1581133480

DOI:10.1145/371920

Chairmen:
Vincent Y. Shen
Hong Kong Univ. of Science and Technology
,
Nobuo Saito
Keio Univ., Japan
,
Michael R. Lyu
Chinese Univ. of Hong Kong, HK
,
Mary Ellen Zurko
Iris Associates,USA

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 April 2001

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WWW01: Hypermedia Track of the 10th International World Wide Web Conference

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Nunes MDorneles C(2023)EDREW - Enhanced Data Representation for Extraction in WebProceedings of the 29th Brazilian Symposium on Multimedia and the Web10.1145/3617023.3617055(230-237)Online publication date: 23-Oct-2023
https://dl.acm.org/doi/10.1145/3617023.3617055
Chen ZMeng WDragut E(2022)Web Record Extraction with InvariantsProceedings of the VLDB Endowment10.14778/3574245.357427616:4(959-972)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.14778/3574245.3574276
Kumaresan URamanujam K(2021)A Framework for Automated Scraping of Structured Data Records From the Deep Web Using Semantic LabelingInternational Journal of Information Retrieval Research10.4018/IJIRR.29083012:1(1-18)Online publication date: 4-Nov-2021
https://doi.org/10.4018/IJIRR.290830
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Automatic information extraction from semi-structured Web pages by pattern discovery

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Automatic information extraction from semi-structured Web pages by pattern discovery

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