Published in

2009 International Conference on Future BioMedical Information Engineering (FBIE)

DOI: 10.1109/fbie.2009.5405911

Links

Tools

Export citation

Search in Google Scholar

An Improved Web Information Summarization Method Using Sentence Similarity-Based Soft Clustering

Journal article published in 2009 by Jun Tang, Xiaojuan Zhao
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

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.