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CLC number: TP391.1

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Received: 2006-07-04

Revision Accepted: 2006-10-07

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Journal of Zhejiang University SCIENCE A 2007 Vol.8 No.1 P.79-87


Using LSA and text segmentation to improve automatic Chinese dialogue text summarization

Author(s):  LIU Chuan-han, WANG Yong-cheng, ZHENG Fei, LIU De-rong

Affiliation(s):  Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200030, China; more

Corresponding email(s):   uuchliu@163.com

Key Words:  Automatic text summarization, Latent semantic analysis (LSA), Text segmentation, Dialogue style, Coherence, Question-answer pairs

LIU Chuan-han, WANG Yong-cheng, ZHENG Fei, LIU De-rong. Using LSA and text segmentation to improve automatic Chinese dialogue text summarization[J]. Journal of Zhejiang University Science A, 2007, 8(1): 79-87.

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%T Using LSA and text segmentation to improve automatic Chinese dialogue text summarization
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%DOI 10.1631/jzus.2007.A0079

T1 - Using LSA and text segmentation to improve automatic Chinese dialogue text summarization
A1 - LIU Chuan-han
A1 - WANG Yong-cheng
A1 - ZHENG Fei
A1 - LIU De-rong
J0 - Journal of Zhejiang University Science A
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SP - 79
EP - 87
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2007.A0079

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.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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