Title :
An improved web information summarization method using Sentence Similarity-Based Soft clustering
Author :
Tang, Jun ; Zhao, Xiaojuan
Author_Institution :
Dept. of Inf. Eng., Hunan Urban Constr. Coll., Xiangtan, China
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.
Keywords :
Internet; Web sites; search engines; Web information summarization method; World Wide Web; document extraction; mixed query sentence; multidocument set; search engine; sentence similarity-based soft clustering; soft clustering algorithm; Biomedical engineering; Biomedical measurements; Clustering algorithms; Clustering methods; Data mining; Educational institutions; Explosions; Search engines; Text processing; Web sites; clustering; sentence similarity; summarization;
Conference_Titel :
BioMedical Information Engineering, 2009. FBIE 2009. International Conference on Future
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-4690-2
Electronic_ISBN :
978-1-4244-4692-6
DOI :
10.1109/FBIE.2009.5405911