One-against-one fuzzy support vector machine text categorization classifier

H. M. Chiang; Tai-Yue Wang

doi:10.1109/IEEM.2008.4738125

One-against-one fuzzy support vector machine text categorization classifier

H. M. Chiang, Tai-Yue Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

The growth of the internet information delivery has made automatic text categorization essential. This investigation explores the challenges of multi-class text categorization using one-against-one fuzzy support vector machine with Reuter's news as the example data. While the fuzzy set theory is incorporated into the OAO-SVM in the classifying module, the influence of the samples with high uncertainty can be decreased as the fuzzy membership functions are to used to weigh the margin of each training vector. The performances of four different membership functions on one-against-one fuzzy support vector machine are measured using the macroaverage performance indices. Analytical results indicate that the proposed method achieves a comparable or better performance than the one-against-one support vector machine.

Original language	English
Title of host publication	2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008
Pages	1519-1523
Number of pages	5
DOIs	https://doi.org/10.1109/IEEM.2008.4738125
Publication status	Published - 2008 Dec 1
Event	2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008 - Singapore, Singapore Duration: 2008 Dec 8 → 2008 Dec 11

Publication series

Name	2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008

Other

Other	2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008
Country/Territory	Singapore
City	Singapore
Period	08-12-08 → 08-12-11

All Science Journal Classification (ASJC) codes

Management Information Systems
Industrial and Manufacturing Engineering

Access to Document

10.1109/IEEM.2008.4738125

Cite this

Chiang, H. M., & Wang, T-Y. (2008). One-against-one fuzzy support vector machine text categorization classifier. In 2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008 (pp. 1519-1523). [4738125] (2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008). https://doi.org/10.1109/IEEM.2008.4738125

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title = "One-against-one fuzzy support vector machine text categorization classifier",

abstract = "The growth of the internet information delivery has made automatic text categorization essential. This investigation explores the challenges of multi-class text categorization using one-against-one fuzzy support vector machine with Reuter's news as the example data. While the fuzzy set theory is incorporated into the OAO-SVM in the classifying module, the influence of the samples with high uncertainty can be decreased as the fuzzy membership functions are to used to weigh the margin of each training vector. The performances of four different membership functions on one-against-one fuzzy support vector machine are measured using the macroaverage performance indices. Analytical results indicate that the proposed method achieves a comparable or better performance than the one-against-one support vector machine.",

author = "Chiang, {H. M.} and Tai-Yue Wang",

year = "2008",

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doi = "10.1109/IEEM.2008.4738125",

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Chiang, HM & Wang, T-Y 2008, One-against-one fuzzy support vector machine text categorization classifier. in 2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008., 4738125, 2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008, pp. 1519-1523, 2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008, Singapore, Singapore, 08-12-08. https://doi.org/10.1109/IEEM.2008.4738125

One-against-one fuzzy support vector machine text categorization classifier. / Chiang, H. M.; Wang, Tai-Yue.

2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008. 2008. p. 1519-1523 4738125 (2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - The growth of the internet information delivery has made automatic text categorization essential. This investigation explores the challenges of multi-class text categorization using one-against-one fuzzy support vector machine with Reuter's news as the example data. While the fuzzy set theory is incorporated into the OAO-SVM in the classifying module, the influence of the samples with high uncertainty can be decreased as the fuzzy membership functions are to used to weigh the margin of each training vector. The performances of four different membership functions on one-against-one fuzzy support vector machine are measured using the macroaverage performance indices. Analytical results indicate that the proposed method achieves a comparable or better performance than the one-against-one support vector machine.

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Chiang HM, Wang T-Y. One-against-one fuzzy support vector machine text categorization classifier. In 2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008. 2008. p. 1519-1523. 4738125. (2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008). https://doi.org/10.1109/IEEM.2008.4738125

One-against-one fuzzy support vector machine text categorization classifier

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