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Multi-document Summarization Based on Cluster using Term Co-occurrence  

Lee, Il-Joo (동원대학 모바일컨텐츠과)
Kim, Min-Koo (아주대학교 컴퓨터공학과)
Publication Information
Journal of KIISE:Software and Applications / v.33, no.2, 2006 , pp. 243-251 More about this Journal
Abstract
In multi-document summarization by means of salient sentence extraction, it is important to remove redundant information. In the removal process, the similarities and differences of sentences are considered. In this paper, we propose a method for multi-document summarization which extracts salient sentences without having redundant sentences by way of cohesive term clustering method that utilizes co-occurrence Information. In the cohesive term clustering method, we assume that each term does not exist independently, but rather it is related to each other in meanings. To find the relations between terms, we cluster sentences according to topics and use the co-occurrence information oi terms in the same topic. We conduct experimental tests with the DUC(Document Understanding Conferences) data. In the tests, our method shows better performance of summarization than other summarization methods which use term co-occurrence information based on term cohesion of document or sentence unit, and simple statistical information.
Keywords
multi-document summarization; co-occurrence information; cohesion;
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Times Cited By KSCI : 2  (Citation Analysis)
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