Cited By
View all- Tseng YLin YLee YHung WLee C(2009)A comparison of methods for detecting hot topicsScientometrics10.1007/s11192-009-1885-x81:1(73-90)Online publication date: 18-Mar-2009
Verifying a Chinese collection for text categorization
Pages 556 - 557
Abstract
This article describes the development of a free test collection for Chinese text categorization. A novel retrieval-based approach was developed to detect duplicates and label inconsistency in this corpus and in Reuters-21578 for comparison. The method was able to detect certain types of similar and/or duplicated documents that were overlooked by an alternative repetition-based method [1]. Experiments showed that effectiveness was not affected by the confusing documents.
References
[1]
Dmitry V. Khmelev and William J. Teahan, "A Repetition Based Measure for Verification of Text Collections and for Text Categorization," ACM SIGIR, 2003, pp.104--110.
[2]
WebGenie 3.23, http://www.webgenie.com.tw
[3]
Amit Singhal, Gerard Salton and Chris Buckley, "Length Normalization in Degraded Text Collections" Symp. on Document Analysis and Info. Retr., 1996, pp. 149--162.
[4]
S. E. Robertson and S. Walker, "Some Simple Effective Approximations to the 2-Poisson Model for Probabilistic Weighted Retrieval," Proc. of ACM SIGIR, 1992, pp.42--49.
Index Terms
- Verifying a Chinese collection for text categorization
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Published In
July 2004
624 pages
ISBN:1581138814
DOI:10.1145/1008992
- General Chair:
- Mark Sanderson,
- Program Chairs:
- Kalervo Järvelin,
- James Allan,
- Peter Bruza
Copyright © 2004 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 25 July 2004
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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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Cited By
View all- Tseng YLin YLee YHung WLee C(2009)A comparison of methods for detecting hot topicsScientometrics10.1007/s11192-009-1885-x81:1(73-90)Online publication date: 18-Mar-2009
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