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

被引：0

作者：

Tang, Jun ^{[1
]}

Zhao, Xiaojuan ^{[1
]}

机构：

[1] Hunan Urban Construct Coll, Dept Informat Engn, Xiangtan, Peoples R China

来源：

2009 INTERNATIONAL CONFERENCE ON FUTURE BIOMEDICAL INFORMATION ENGINEERING (FBIE 2009) | 2009年

关键词：

summarization; clustering; sentence similarity;

D O I：

10.1109/FBIE.2009.5405911

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

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.

引用

页码：292 / 295

页数：4