• Title of article

    Advanced document retrieval techniques for patent research Original Research Article

  • Author/Authors

    James F. Ryley، نويسنده , , Jeff Saffer، نويسنده , , Andy Gibbs، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2008
  • Pages
    6
  • From page
    238
  • To page
    243
  • Abstract
    Latent semantic indexing (LSI) can be used in patent searching to overcome drawbacks of Boolean searching and to give more accurate retrieval. LSI combines the vector space model (VSM) of document retrieval with single value decomposition (SVD), using linear algebra techniques to uncover word relationships in the text. Results can be enhanced by using text clustering and tailoring SVD parameters to the specific corpus, in this case, patents, and by employing techniques to address ambiguities in language.
  • Keywords
    LSI , Vector space model , VSM , Single value decomposition , text mining , Clustering , Patents , SVD , Latent semantic indexing
  • Journal title
    World Patent Information
  • Serial Year
    2008
  • Journal title
    World Patent Information
  • Record number

    1230429