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http://dx.doi.org/10.3745/KIPSTB.2006.13B.2.149

Document Summarization Based on Sentence Clustering Using Graph Division  

Lee Il-Joo (동원대학 모바일컨텐츠과)
Kim Min-Koo (아주대학교 정보 및 컴퓨터공학부)
Publication Information
The KIPS Transactions:PartB / v.13B, no.2, 2006 , pp. 149-154 More about this Journal
Abstract
The main purpose of document summarization is to reduce the complexity of documents that are consisted of sub-themes. Also it is to create summarization which includes the sub-themes. This paper proposes a summarization system which could extract any salient sentences in accordance with sub-themes by using graph division. A document can be represented in graphs by using chosen representative terms through term relativity analysis based on co-occurrence information. This graph, then, is subdivided to represent sub-themes through connected information. The divided graphs are types of sentence clustering which shows a close relationship. When salient sentences are extracted from the divided graphs, summarization consisted of core elements of sentences from the sub-themes can be produced. As a result, the summarization quality will be improved.
Keywords
Document Summarization; Term Relation; Sentence Clustering; Graph Division;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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