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Analysis of Sentence Ordering Based on Support Vector Machine

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5 Author(s)
Gongfu Peng ; Comput. Sch., Wuhan Univ., Wuhan, China ; Yanxiang He ; Ye Tian ; Yingsheng Tian
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In this paper, we present a practical method of sentence ordering in multi-document summarization tasks of Chinese language. By using Support Vector Machine (SVM), we classify the sentences of a summary into several groups in rough position according to the source documents. Then we adjust the sentence sequence of each group according to the estimation of directional relativity of adjacent sentences, and find the sequence of each group. Finally, we connect the sequences of different groups to generate the final order of the summary. Experimental results indicate that this method works better than most existing methods of sentence ordering.

Published in:

Knowledge Engineering and Software Engineering, 2009. KESE '09. Pacific-Asia Conference on

Date of Conference:

19-20 Dec. 2009