DocumentCode :
511162
Title :
Analysis of Sentence Ordering Based on Support Vector Machine
Author :
Peng, Gongfu ; He, Yanxiang ; Tian, Ye ; Tian, Yingsheng ; Wen, Weidong
Author_Institution :
Comput. Sch., Wuhan Univ., Wuhan, China
fYear :
2009
fDate :
19-20 Dec. 2009
Firstpage :
25
Lastpage :
27
Abstract :
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.
Keywords :
document handling; linguistics; natural language processing; support vector machines; Chinese language; multidocument summarization tasks; sentence ordering analysis; sentences classification; support vector machine; Clustering algorithms; Helium; Humans; Knowledge engineering; Natural languages; Software engineering; Support vector machine classification; Support vector machines; Writing; SVM; Sentence Ordering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Knowledge Engineering and Software Engineering, 2009. KESE '09. Pacific-Asia Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-0-7695-3916-4
Type :
conf
DOI :
10.1109/KESE.2009.14
Filename :
5383630
Link To Document :
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