• DocumentCode
    1606448
  • Title

    Multi-document summarization using sentence clustering

  • Author

    Gupta, V.K. ; Siddiqui, Tanveer J.

  • Author_Institution
    Samsung India Software Oper., Bangalore, India
  • fYear
    2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents an approach to query focused multi document summarization by combining single document summary using sentence clustering. Both syntactic and semantic similarity between sentences is used for clustering. Single document summary is generated using document feature, sentence reference index feature, location feature and concept similarity feature. Sentences from single document summaries are clustered and top most sentences from each cluster are used for creating multi-document summary. We observed an average F-measure of 0.33774 on DUC 2002 multi-document dataset, which is comparable to three best performing systems reported on the same dataset.
  • Keywords
    document handling; grammars; pattern clustering; pattern matching; F-measure; concept similarity feature; document feature; location feature; multidocument dataset; multidocument summarization; semantic similarity; sentence clustering; sentence reference index feature; single document summary; syntactic similarity; Cancer; Feature extraction; Indexes; Information retrieval; Semantics; Syntactics; Vectors; DUC-2002; Multi document summarization; feature extraction; sentence clustering method;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Human Computer Interaction (IHCI), 2012 4th International Conference on
  • Conference_Location
    Kharagpur
  • Print_ISBN
    978-1-4673-4367-1
  • Type

    conf

  • DOI
    10.1109/IHCI.2012.6481826
  • Filename
    6481826