Article

Context-based methods for text categorisation

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SIGIR '04: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval

Pages 578 - 579

https://doi.org/10.1145/1008992.1009129

Published: 25 July 2004 Publication History

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Abstract

We propose several context-based methods for text categorization. One method, a small modification to the PPM compression-based model which is known to significantly degrade compression performance, counter-intuitively has the opposite effect on categorization performance. Another method, called C-measure, simply counts the presence of higher order character contexts, and outperforms all other approaches investigated.

References

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S. Dumais, J. Platt, D. Heckerman, and M. Sahami. Inductive learning algorithms and representations for text categorization. In Proceedings Int. Conf. on Inform. and Know. Management pages 148--155, 1998.

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D. V. Khmelev and W. J. Teahan. A repetition based measure for verification of text collections and for text categorization. In Proceedings of SIGIR 2003 pages 104--110, 2003.

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W. J. Teahan and D. J. Harper. Using compression based language models for text categorization. In Lang. Modeling for Information Retrieval pages 141--65. Kluwer Academic Publishers, 2003.

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Cited By

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Abadi SMohammadi AKoohi S(2023)An automated ultra-fast, memory-efficient, and accurate method for viral genome classificationJournal of Biomedical Informatics10.1016/j.jbi.2023.104316139(104316)Online publication date: Mar-2023
https://doi.org/10.1016/j.jbi.2023.104316
Fabijanska AGrabowski S(2019)Viral Genome Deep ClassifierIEEE Access10.1109/ACCESS.2019.29236877(81297-81307)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2923687
Vo DOck C(2015)Learning to classify short text from scientific documents using topic models with various types of knowledgeExpert Systems with Applications: An International Journal10.1016/j.eswa.2014.09.03142:3(1684-1698)Online publication date: 15-Feb-2015
https://dl.acm.org/doi/10.1016/j.eswa.2014.09.031
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Index Terms

Context-based methods for text categorisation
1. Information systems
  1. Information systems applications

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Information

Published In

SIGIR '04: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval

July 2004

624 pages

ISBN:1581138814

DOI:10.1145/1008992

General Chair:
Mark Sanderson
University of Sheffield (UK)
,
Program Chairs:
Kalervo Järvelin
University of Tampere (Finland)
,
James Allan
University of Massachusetts (USA)
,
Peter Bruza
Distributed Systems Technology Centre (Australia)

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: 25 July 2004

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SIGIR04

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SIGIR04: The 27th ACM/SIGIR International Symposium on Information Retrieval 2004

July 25 - 29, 2004

Sheffield, United Kingdom

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Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Abadi SMohammadi AKoohi S(2023)An automated ultra-fast, memory-efficient, and accurate method for viral genome classificationJournal of Biomedical Informatics10.1016/j.jbi.2023.104316139(104316)Online publication date: Mar-2023
https://doi.org/10.1016/j.jbi.2023.104316
Fabijanska AGrabowski S(2019)Viral Genome Deep ClassifierIEEE Access10.1109/ACCESS.2019.29236877(81297-81307)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2923687
Vo DOck C(2015)Learning to classify short text from scientific documents using topic models with various types of knowledgeExpert Systems with Applications: An International Journal10.1016/j.eswa.2014.09.03142:3(1684-1698)Online publication date: 15-Feb-2015
https://dl.acm.org/doi/10.1016/j.eswa.2014.09.031
Ziegelmayer DSchrader R(2012)Sentiment Polarity Classification Using Statistical Data Compression ModelsProceedings of the 2012 IEEE 12th International Conference on Data Mining Workshops10.1109/ICDMW.2012.43(731-738)Online publication date: 10-Dec-2012
https://dl.acm.org/doi/10.1109/ICDMW.2012.43
Thomas DTeahan WKraaij Wde Vries AClarke CFuhr NKando N(2007)Text categorization for streamsProceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval10.1145/1277741.1277975(907-907)Online publication date: 23-Jul-2007
https://dl.acm.org/doi/10.1145/1277741.1277975

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Cross-lingual text categorization: Conquering language boundaries in globalized environments

Arabic Text Categorization Based on Arabic Wikipedia

Context-sensitive learning methods for text categorization