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http://dx.doi.org/10.6109/jkiice.2012.16.12.2607

Generic Document Summarization using Coherence of Sentence Cluster and Semantic Feature  

Park, Sun (목포대학교 정보산업연구소)
Lee, Yeonwoo (목포대학교 정보통신학과)
Shim, Chun Sik (목포대학교 조선공학과)
Lee, Seong Ro (목포대학교 정보전자공학과)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.16, no.12, 2012 , pp. 2607-2613 More about this Journal
Abstract
The results of inherent knowledge based generic summarization are influenced by the composition of sentence in document set. In order to resolve the problem, this papser propses a new generic document summarization which uses clustering of semantic feature of document and coherence of document cluster. The proposed method clusters sentences using semantic feature deriving from NMF(non-negative matrix factorization), which it can classify document topic group because inherent structure of document are well represented by the sentence cluster. In addition, the method can improve the quality of summarization because the importance sentences are extracted by using coherence of sentence cluster and the cluster refinement by re-cluster. The experimental results demonstrate appling the proposed method to generic summarization achieves better performance than generic document summarization methods.
Keywords
generic summarization; semantic feature; coherence of sentence cluster; NMF(non-negative matrix factorization); kmeans clustering;
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