• DocumentCode
    1909297
  • Title

    A Rough Concept Recognition Approach for Information Retrieval Based on Latent Semantic Analysis

  • Author

    Wang, Yi-chuan ; Guo, Yan-hui ; Li, Lei

  • Author_Institution
    Center for Intell. Sci. & Technol. Res., Beijing Univ. of Posts & Telecommun., Beijing
  • fYear
    2007
  • fDate
    Aug. 30 2007-Sept. 1 2007
  • Firstpage
    90
  • Lastpage
    95
  • Abstract
    This paper presents an information retrieval approach which uses a rough concept clustering in conjunction with Latent Semantic Analysis(LSA) to provide better document retrieval results matched to queries. The conceptual context defined in this article can be local, so no domain expert has to be involved in this approach. Our experiment consists of word clustering by similarity and rough concept recognition, associated to a basic LSA retrieval system. Our information retrieval process is illustrated through our experimentation model and results are compared in two different aspects. Experiment results show that retrieval performance benefit can be gained from this approach and further performance benefits can also be obtained according to the further work, which needs researching about parameter settings and algorithm development.
  • Keywords
    information retrieval; pattern clustering; word processing; information retrieval approach; latent semantic analysis; rough concept recognition approach; word clustering; Clustering algorithms; Clustering methods; Content based retrieval; Information analysis; Information retrieval; Matrix decomposition; Ontologies; Partitioning algorithms; Performance analysis; Target recognition; Concept Clustering Information Retrieval(IR); Latent Semantic Analysis(LSA);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Language Processing and Knowledge Engineering, 2007. NLP-KE 2007. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-1610-3
  • Electronic_ISBN
    978-1-4244-1611-0
  • Type

    conf

  • DOI
    10.1109/NLPKE.2007.4368016
  • Filename
    4368016