By Topic

An improved web information summarization method using Sentence Similarity-Based Soft clustering

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

2 Author(s)
Jun Tang ; Dept. of Inf. Eng., Hunan Urban Constr. Coll., Xiangtan, China ; Xiaojuan Zhao

For the explosion of information in the World Wide Web, this paper proposed a new method of web news summarization via soft clustering algorithm. It used search engine to extract relevant documents, and mixed query sentence into sentences set which segmented from multi-document set, then this paper adopted efficient soft cluster algorithm SSSC (sentence similarity-based soft clustering) to cluster all the sentences. Experimental result shows that the proposed summarization method can improve the performance of summary, soft clustering algorithm is efficient.

Published in:

BioMedical Information Engineering, 2009. FBIE 2009. International Conference on Future

Date of Conference:

13-14 Dec. 2009