• DocumentCode
    2919422
  • Title

    A Latent Semantic Analysis Based Method of Getting the Category Attribute of Words

  • Author

    Jiang, Zongli ; Lu, Changdong

  • Author_Institution
    Lab. of Comput. Software & Theor., Beijing Univ. of Technol., Beijing
  • fYear
    2009
  • fDate
    20-22 Feb. 2009
  • Firstpage
    141
  • Lastpage
    146
  • Abstract
    Current search engines have two problems, losing useful information and including useless information. These two problems are aroused by the keyword matching retrieval model, which is adopted by almost all search engines. We introduce the conception of category attribute of a word. According to the category attribute of a word, the useless results can be removed from the search results and the retrieval efficiency will be improved. A latent semantic analysis based method of getting the category attribute of the word is presented in this paper, which is proved to be effective by experiment. Latent semantic analysis is a method that can discover the underlying semantic relation between words and documents. Singular value decomposition is used in latent semantic analysis to analyze the words and documents and get the semantic relation finally.
  • Keywords
    information retrieval; search engines; singular value decomposition; keyword matching retrieval model; latent semantic analysis; retrieval efficiency; search engines; singular value decomposition; word category attribute retrieval; Information analysis; Information retrieval; Internet; Laboratories; Missiles; Search engines; Singular value decomposition; Software; Text categorization; Web pages; information retrieval; latent semantic analysis; search engine; text categorization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Computer Technology, 2009 International Conference on
  • Conference_Location
    Macau
  • Print_ISBN
    978-0-7695-3559-3
  • Type

    conf

  • DOI
    10.1109/ICECT.2009.19
  • Filename
    4795937