A Multi-Label Chinese Text Categorization System Based on Boosting Algorithm

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Fourth International Conference on Computer and Information Technology (CIT'04)

Wuhan, China

September 14-September 16

ISBN: 0-7695-2216-5

	ASCII Text	x
	Junli Chen, Xuezhong Zhou, Zhaohui Wu, "A Multi-Label Chinese Text Categorization System Based on Boosting Algorithm," Computer and Information Technology, International Conference on, pp. 1153-1158, Fourth International Conference on Computer and Information Technology (CIT'04), 2004.

	BibTex	x
	@article{ 10.1109/CIT.2004.1357350, author = {Junli Chen and Xuezhong Zhou and Zhaohui Wu}, title = {A Multi-Label Chinese Text Categorization System Based on Boosting Algorithm}, journal ={Computer and Information Technology, International Conference on}, volume = {0}, year = {2004}, isbn = {0-7695-2216-5}, pages = {1153-1158}, doi = {http://doi.ieeecomputersociety.org/10.1109/CIT.2004.1357350}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer and Information Technology, International Conference on TI - A Multi-Label Chinese Text Categorization System Based on Boosting Algorithm SN - 0-7695-2216-5 SP1153 EP1158 A1 - Junli Chen, A1 - Xuezhong Zhou, A1 - Zhaohui Wu, PY - 2004 KW - null VL - 0 JA - Computer and Information Technology, International Conference on ER -

Junli Chen, Zhejiang University

Xuezhong Zhou, Zhejiang University

Zhaohui Wu, Zhejiang University

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CIT.2004.1357350

This paper presents a multi-label Chinese text categorization system based on Chinese character features and boosting algorithm. This system has been successfully evaluated on the TCM-MED dataset provided by China academy of Traditional Chinese Medicine (TCM) and the Reuters-21578 benchmark. We suggest that the TCM-MED dataset can be used as a standard corpus for the Chinese text categorization tasks. We have also carried out experiments to compare the performance of the boosting algorithm with two other traditional algorithms on the same datasets. The results indicate that for the design of a multi-label Chinese text categorization system, the boosting algorithm has a high performance and outperforms the other two algorithms.

Citation:

Junli Chen, Xuezhong Zhou, Zhaohui Wu, "A Multi-Label Chinese Text Categorization System Based on Boosting Algorithm," cit, pp.1153-1158, Fourth International Conference on Computer and Information Technology (CIT'04), 2004

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