• Title/Summary/Keyword: wikipedai

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User-based Document Summarization using Non-negative Matrix Factorization and Wikipedia (비음수행렬분해와 위키피디아를 이용한 사용자기반의 문서요약)

  • Park, Sun;Jeong, Min-A;Lee, Seong-Ro
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.2
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    • pp.53-60
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    • 2012
  • In this paper, we proposes a new document summarization method using the expanded query by wikipedia and the semantic feature representing inherent structure of document set. The proposed method can expand the query from user's initial query using the relevance feedback based on wikipedia in order to reflect the user require. It can well represent the inherent structure of documents using the semantic feature by the non-negative matrix factorization (NMF). In addition, it can reduce the semantic gap between the user require and the result of document summarization to extract the meaningful sentences using the expanded query and semantic features. The experimental results demonstrate that the proposed method achieves better performance than the other methods to summary document.