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http://dx.doi.org/10.6109/jkiice.2012.16.3.533

Document Summarization using Pseudo Relevance Feedback and Term Weighting  

Kim, Chul-Won (호남대학교 컴퓨터공학과)
Park, Sun (목포대학교 정보산업연구소)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.16, no.3, 2012 , pp. 533-540 More about this Journal
Abstract
In this paper, we propose a document summarization method using the pseudo relevance feedback and the term weighting based on semantic features. The proposed method can minimize the user intervention to use the pseudo relevance feedback. It also can improve the quality of document summaries because the inherent semantic of the sentence set are well reflected by term weighting derived from semantic feature. In addition, it uses the semantic feature of term weighting and the expanded query to reduce the semantic gap between the user's requirement and the result of proposed method. The experimental results demonstrate that the proposed method achieves better performant than other methods without term weighting.
Keywords
document summarization; pseudo relevance feedback; semantic features; term weighting; non-negative matrix factorization (NMF) Open Access;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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