By Topic

Analysis of Sentence Ordering Based on Support Vector Machine

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Gongfu Peng ; Comput. Sch., Wuhan Univ., Wuhan, China ; Yanxiang He ; Ye Tian ; Yingsheng Tian
more authors

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