• DocumentCode
    3060841
  • Title

    Comparative evaluation on concept approximation approaches

  • Author

    Deogun, Jitender ; Jiang, Liying

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Nebraska Univ., Lincoln, NE, USA
  • fYear
    2005
  • fDate
    8-10 Sept. 2005
  • Firstpage
    438
  • Lastpage
    443
  • Abstract
    Formal concept analysis (FCA) is a method for deriving conceptual structures out of data that are represented as objects with features. FCA discovers dependencies within the data based on the relation among objects and features. However, not every pair of objects and features defines a concept. Concept approximation is to find the best or closest concept(s) to approximate a pair of objects and features. Concept approximation is significant in that under the circumstances that we can not find a concept, using concept approximation will give the best or most possible solution. In this paper, we evaluate three approaches through experiments in the application of document retrieval. We provide analysis of these approaches and give our concluding remarks.
  • Keywords
    approximation theory; data analysis; data mining; information retrieval; set theory; concept approximation approach; conceptual structures; document retrieval application; formal concept analysis; Computer science; Data analysis; Data engineering; Diseases; Government; Information retrieval; Mathematics; Performance evaluation; Set theory; US Department of Agriculture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems Design and Applications, 2005. ISDA '05. Proceedings. 5th International Conference on
  • Print_ISBN
    0-7695-2286-6
  • Type

    conf

  • DOI
    10.1109/ISDA.2005.35
  • Filename
    1578824