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2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery
A Fusion of Multiple Classifiers Approach Based on Reliability function for Text Categorization
October 18-October 20
ISBN: 978-0-7695-3305-6
| ASCII Text | x | ||
| Qingxuan Chen, Dequan Zheng, Tiejun Zhao, Sheng Li, "A Fusion of Multiple Classifiers Approach Based on Reliability function for Text Categorization," Fuzzy Systems and Knowledge Discovery, Fourth International Conference on, vol. 2, pp. 338-342, 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery, 2008. | |||
| BibTex | x | ||
| @article{ 10.1109/FSKD.2008.373, author = {Qingxuan Chen and Dequan Zheng and Tiejun Zhao and Sheng Li}, title = {A Fusion of Multiple Classifiers Approach Based on Reliability function for Text Categorization}, journal ={Fuzzy Systems and Knowledge Discovery, Fourth International Conference on}, volume = {2}, year = {2008}, isbn = {978-0-7695-3305-6}, pages = {338-342}, doi = {http://doi.ieeecomputersociety.org/10.1109/FSKD.2008.373}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Fuzzy Systems and Knowledge Discovery, Fourth International Conference on TI - A Fusion of Multiple Classifiers Approach Based on Reliability function for Text Categorization SN - 978-0-7695-3305-6 SP338 EP342 A1 - Qingxuan Chen, A1 - Dequan Zheng, A1 - Tiejun Zhao, A1 - Sheng Li, PY - 2008 KW - main classifier KW - reliability function KW - multiple classifiers KW - text categorization VL - 2 JA - Fuzzy Systems and Knowledge Discovery, Fourth International Conference on ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/FSKD.2008.373
With the development of Internet and the rapid expansion of electronic resource, text classification technology is becoming an effective organization and management tool to deal with information. In this paper, a method for text categorization based on the fusion of multiple classifiers was presented, reliability function was introduction to select the text that hard to give determine by the main classifier, for these texts, multiple classifiers were used to give the determine which category the unlabeled documents belong to by voting. Experiments showed that the performance of text classification improved by the proposed method. Compared with single classifier, this method achieved better performance, only increasing a small amount of time than using single main classifier. Besides this, this method is more stable than using single classifier for text categorization task, especially when using different corpuses to check the performance of various methods.
Index Terms:
main classifier, reliability function, multiple classifiers, text categorization
Citation:
Qingxuan Chen, Dequan Zheng, Tiejun Zhao, Sheng Li, "A Fusion of Multiple Classifiers Approach Based on Reliability function for Text Categorization," fskd, vol. 2, pp.338-342, 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery, 2008
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