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Using LSA and text segmentation to improve automatic Chinese dialogue text summarization 被引量:3
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作者 liu chuan-han WANG Yong-cheng +1 位作者 ZHENG Fei liu De-rong 《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 SCIE EI CAS CSCD 2007年第1期79-87,共9页
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 ... 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 ques-tion-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. 展开更多
关键词 汉语对话 自动文本摘要 隐含语义分析 文本分析 对话方式
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