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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2005, Vol. 6 Issue ( 1): 8-    DOI: 10.1631/jzus.2005.A0049
    
An improved TF-IDF approach for text classification
ZHANG Yun-tao, GONG Ling, WANG Yong-cheng
Network & Information Center, School of Electronic & Information Technology, Shanghai Jiaotong University, Shanghai 200030, China
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Abstract  This paper presents a new improved term frequency/inverse document frequency (TF-IDF) approach which uses confidence, support and characteristic words to enhance the recall and precision of text classification. Synonyms defined by a lexicon are processed in the improved TF-IDF approach. We detailedly discuss and analyze the relationship among confidence, recall and precision. The experiments based on science and technology gave promising results that the new TF-IDF approach improves the precision and recall of text classification compared with the conventional TF-IDF approach.

Key words： Term frequency/inverse document frequency (TF-IDF)      Text classification      Confidence      Support      Characteristic words     
Received: 05 December 2003     
CLC:  TP31  
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ZHANG Yun-tao
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GONG Ling
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ZHANG Yun-tao, GONG Ling, WANG Yong-cheng. An improved TF-IDF approach for text classification. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2005, 6( 1): 8-.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2005.A0049     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2005/V6/I 1/8

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