• DocumentCode
    428584
  • Title

    Meta latent semantic analysis

  • Author

    Simina, Marin ; Barbu, Costin

  • Author_Institution
    Dept. of CIS, Loyola Univ., New Orleans, LA, USA
  • Volume
    4
  • fYear
    2004
  • fDate
    10-13 Oct. 2004
  • Firstpage
    3720
  • Abstract
    Meta latent semantic analysis (MLSA) is a novel approach to automated document analysis and indexing which relies on symbolic ontologies to further enhance the traditional probabilistic latent semantic analysis (LSA) of documents. While LSA is able to discover clusters of related terms and documents in a given collection of documents, the proposed MLSA is able to meta-cluster such clusters by taking into account existing symbolic ontologies relevant for the analyzed collections of documents. Such an approach can be successfully used to improve the performance of fast LSA by random projection.
  • Keywords
    document handling; indexing; ontologies (artificial intelligence); semantic networks; automated document analysis; meta latent semantic analysis; meta-cluster; random projection; symbolic ontologies; traditional probabilistic latent semantic analysis; Computational Intelligence Society; Indexing; Information analysis; Information retrieval; Ontologies; Sampling methods; Singular value decomposition; Text analysis; User interfaces;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2004 IEEE International Conference on
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-8566-7
  • Type

    conf

  • DOI
    10.1109/ICSMC.2004.1400922
  • Filename
    1400922
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=428584