• DocumentCode
    2457288
  • Title

    Macro-clustering: improved information retrieval using fuzzy logic

  • Author

    Liyanage, Harshana ; Bandara, G.E.M.D.C.

  • Author_Institution
    Dept. of Comput. Sci. & Stat., Peradeniya Univ., Sri Lanka
  • fYear
    2004
  • fDate
    2-4 Sept. 2004
  • Firstpage
    413
  • Lastpage
    418
  • Abstract
    The World Wide Web contains a huge amount of unclassified data and its continuous growth has made it a complex domain for information retrieval. Current Web information retrieval (IR) systems (i.e., search engines) very often overload the user with irrelevant search results. This has forced the user to perform a certain level of analysis on the results returned. Web IR systems are currently one of the most researched areas in the computer industry. So far there have been many attempts to incorporate soft computing techniques such as fuzzy logic, neural networks, genetic algorithms, etc. This work focuses on how fuzzy logic can be introduced to IR systems. The current applications of fuzzy techniques are analyzed and a concept called "macro-clustering" is introduced as a solution for optimizing results of generalized search queries.
  • Keywords
    Internet; data mining; fuzzy logic; information retrieval; World Wide Web; data mining; fuzzy logic; fuzzy macroclustering; information retrieval; soft computing techniques; Application software; Computer industry; Computer networks; Fuzzy logic; Genetic algorithms; Information retrieval; Neural networks; Performance analysis; Search engines; Web sites;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control, 2004. Proceedings of the 2004 IEEE International Symposium on
  • ISSN
    2158-9860
  • Print_ISBN
    0-7803-8635-3
  • Type

    conf

  • DOI
    10.1109/ISIC.2004.1387719
  • Filename
    1387719