• DocumentCode
    2329053
  • Title

    Association rules mining on concept lattice using domain knowledge

  • Author

    Wang, De-Xing ; Hu, Xue-Gang ; Liu, Xiao-Ping ; Wang, Hao

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Hefei Univ. of Technol., China
  • Volume
    4
  • fYear
    2005
  • fDate
    18-21 Aug. 2005
  • Firstpage
    2151
  • Abstract
    Large databases make computation of knowledge discovery more and more expensive, then it is proved counter-evidently that domain knowledge hidden in the database, can often guide and restrict the search for interesting knowledge, play more roles in guiding knowledge discovery in databases. While concept lattice represents knowledge on the Hass diagram with the relationships between entities and attributes, then the knowledge can be shown with hierarchical structure on the Hass diagram, thus it is properly applied to the description of association rules mining in databases. In the paper, we discuss how to use domain knowledge to guide association rules mining on concept lattice, association rules mining on which can be shown that it represents the rules more visual, vivid and concise, if using domain knowledge, we can reduce the search space, avoid blocking unexpected discoveries, so knowledge discovery can be improved effectively.
  • Keywords
    data mining; very large databases; Hass diagram; association rules mining; concept lattice; domain knowledge; knowledge discovery; search space; Access control; Association rules; Computer science; Data analysis; Data mining; Dictionaries; Lattices; Statistics; Testing; Visual databases; Data mining; association rule; concept lattice; domain knowledge;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
  • Conference_Location
    Guangzhou, China
  • Print_ISBN
    0-7803-9091-1
  • Type

    conf

  • DOI
    10.1109/ICMLC.2005.1527301
  • Filename
    1527301