Document Summarization Based on Sentence Clustering Using Graph Division 


Vol. 13,  No. 2, pp. 149-154, Apr.  2006
10.3745/KIPSTB.2006.13.2.149


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  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.

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[IEEE Style]

I. J. Lee and M. K. Kim, "Document Summarization Based on Sentence Clustering Using Graph Division," The KIPS Transactions:PartB , vol. 13, no. 2, pp. 149-154, 2006. DOI: 10.3745/KIPSTB.2006.13.2.149.

[ACM Style]

Il Joo Lee and Min Koo Kim. 2006. Document Summarization Based on Sentence Clustering Using Graph Division. The KIPS Transactions:PartB , 13, 2, (2006), 149-154. DOI: 10.3745/KIPSTB.2006.13.2.149.

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