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Article

Combining multiple classifiers for text categorization

Authors:

Khalid Al-Kofahi,

Peter JacksonAuthors Info & Claims

CIKM '01: Proceedings of the tenth international conference on Information and knowledge management

Pages 97 - 104

https://doi.org/10.1145/502585.502603

Published: 05 October 2001 Publication History

Abstract

A major problem facing online information services is how to index and supplement large document collections with respect to a rich set of categories. We focus upon the routing of case law summaries to various secondary law volumes in which they should be cited. Given the large number (> 13,000) of closely related categories, this is a challenging task that is unlikely to succumb to a single algorithmic solution. Our fully implemented and recently deployed system shows that a superior classification engine for this task can be constructed from a combination of classifiers. The multi-classifier approach helps us leverage all the relevant textual features and meta data, and appears to generalize to related classification tasks.

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Cited By

Korkontzelos IPiliouras DDowsey AAnaniadou S(2015)Boosting drug named entity recognition using an aggregate classifierArtificial Intelligence in Medicine10.1016/j.artmed.2015.05.00765:2(145-153)Online publication date: 1-Oct-2015
https://dl.acm.org/doi/10.1016/j.artmed.2015.05.007
Tripathi NOakes MWermter S(2012)A fast subspace text categorization method using parallel classifiersProceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part II10.1007/978-3-642-28601-8_12(132-143)Online publication date: 11-Mar-2012
https://dl.acm.org/doi/10.1007/978-3-642-28601-8_12
Tripathi NOakes MWermter S(2011)Semantic subspace learning for text classification using hybrid intelligent techniquesInternational Journal of Hybrid Intelligent Systems10.5555/2010580.20105858:2(99-114)Online publication date: 1-Apr-2011
https://dl.acm.org/doi/10.5555/2010580.2010585
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Combining multiple classifiers for text categorization

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Published In

cover image ACM Conferences

CIKM '01: Proceedings of the tenth international conference on Information and knowledge management

October 2001

616 pages

ISBN:1581134363

DOI:10.1145/502585

Editors:
Henrique Paques
Georgia Institute of Technology
,
Ling Liu
Georgia Institute of Technology
,
David Grossman
Illinois Institute of Technology
,
General Chair:
Calton Pu
Georgia Institute of Technology

Copyright © 2001 ACM.

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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Publication History

Published: 05 October 2001

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October 5 - 10, 2001

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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

Korkontzelos IPiliouras DDowsey AAnaniadou S(2015)Boosting drug named entity recognition using an aggregate classifierArtificial Intelligence in Medicine10.1016/j.artmed.2015.05.00765:2(145-153)Online publication date: 1-Oct-2015
https://dl.acm.org/doi/10.1016/j.artmed.2015.05.007
Tripathi NOakes MWermter S(2012)A fast subspace text categorization method using parallel classifiersProceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part II10.1007/978-3-642-28601-8_12(132-143)Online publication date: 11-Mar-2012
https://dl.acm.org/doi/10.1007/978-3-642-28601-8_12
Tripathi NOakes MWermter S(2011)Semantic subspace learning for text classification using hybrid intelligent techniquesInternational Journal of Hybrid Intelligent Systems10.5555/2010580.20105858:2(99-114)Online publication date: 1-Apr-2011
https://dl.acm.org/doi/10.5555/2010580.2010585
Lu QConrad JAl-Kofahi KKeenan W(2011)Legal document clustering with built-in topic segmentationProceedings of the 20th ACM international conference on Information and knowledge management10.1145/2063576.2063636(383-392)Online publication date: 24-Oct-2011
https://dl.acm.org/doi/10.1145/2063576.2063636
Richards RBruce TBertot JNahon KChun SLuna-Reyes LAtluri V(2011)Examples of specialized legal metadata adapted to the digital environment, from the U.S. code of federal regulationsProceedings of the 12th Annual International Digital Government Research Conference: Digital Government Innovation in Challenging Times10.1145/2037556.2037594(229-234)Online publication date: 12-Jun-2011
https://dl.acm.org/doi/10.1145/2037556.2037594
Richards RBruce TAshley Kvan Engers T(2011)Adapting specialized legal metadata to the digital environmentProceedings of the 13th International Conference on Artificial Intelligence and Law10.1145/2018358.2018377(126-130)Online publication date: 6-Jun-2011
https://dl.acm.org/doi/10.1145/2018358.2018377
Choi YPark S(2010)Reinforcement Post-Processing and Feedback Algorithm for Optimal Combination in Bottom-Up Hierarchical ClassificationThe KIPS Transactions:PartB10.3745/KIPSTB.2010.17B.2.13917B:2(139-148)Online publication date: 30-Apr-2010
https://doi.org/10.3745/KIPSTB.2010.17B.2.139
Ben-Dov MFeldman R(2010)Text Mining and Information ExtractionData Mining and Knowledge Discovery Handbook10.1007/978-0-387-09823-4_42(809-835)Online publication date: 7-Jul-2010
https://doi.org/10.1007/978-0-387-09823-4_42
Jackson P(2007)Generating Value from Textual DiscoveryProceedings of the 7th international conference on Computational Science, Part III: ICCS 200710.1007/978-3-540-72588-6_123(746-753)Online publication date: 27-May-2007
https://dl.acm.org/doi/10.1007/978-3-540-72588-6_123
Papadakis NLitke ASkoutas DVarvarigou T(2006)MEMPHISJournal of Systems Architecture: the EUROMICRO Journal10.1016/j.sysarc.2005.05.00752:6(315-331)Online publication date: 1-Jun-2006
https://dl.acm.org/doi/10.1016/j.sysarc.2005.05.007
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