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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2007, Vol. 8 Issue (1 ): 12-    DOI: 10.1631/jzus.2007.A0079
    
Using LSA and text segmentation to improve automatic Chinese dialogue text summarization
LIU Chuan-han, WANG Yong-cheng, ZHENG Fei, LIU De-rong
Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200030, China; Center for Biomimetic Sensing and Control Research, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China
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Abstract  Automatic Chinese text summarization for dialogue style is a relatively new research area. In this paper, Latent Semantic Analysis (LSA) is first used to extract semantic knowledge from a given document, all question paragraphs are identified, an automatic text segmentation approach analogous to TextTiling is exploited to improve the precision of correlating question paragraphs and answer paragraphs, and finally some “important” sentences are extracted from the generic content and the question-answer pairs to generate a complete summary. Experimental results showed that our approach is highly efficient and improves significantly the coherence of the summary while not compromising informativeness.

Key words： Automatic text summarization      Latent semantic analysis (LSA)      Text segmentation      Dialogue style      Coherence      Question-answer pairs     
Received: 04 July 2006     
CLC:  TP391.1  
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LIU Chuan-han
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Cite this article:

LIU Chuan-han, WANG Yong-cheng, ZHENG Fei, LIU De-rong. Using LSA and text segmentation to improve automatic Chinese dialogue text summarization. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2007, 8(1 ): 12-.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2007.A0079     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2007/V8/I1 /12

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