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

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.