• DocumentCode
    3121315
  • Title

    Research on the process with closure after mining in KDD

  • Author

    Huang, Shao-jun ; Liu, Yu-zhen ; Yang, Tian-liang

  • Author_Institution
    Dept. of Comput., Anshan Univ. of Sci. & Technol., China
  • Volume
    4
  • fYear
    2002
  • fDate
    4-5 Nov. 2002
  • Firstpage
    2036
  • Abstract
    To guarantee the quality of knowledge base, how to process a great deal of new discovered and meaningless hypotheses is very important. If the knowledge in knowledge base is represented in produced rule, and the conditions of the rule and all the results that the rule can reach by reference mechanism compose a set, then the set is a closure of the knowledge base. Acquiring the closure of a knowledge base can acquire. minimum knowledge base, and then the new discovered hypotheses can be processed by using minimum knowledge base. The experiments demonstrate that the process with closure after mining in KDD to identify the hypotheses is effective and efficient.
  • Keywords
    data mining; deductive databases; KDD; closure; data mining; databases; knowledge base quality; knowledge discovery; minimum knowledge base; Algorithm design and analysis; Artificial intelligence; Concrete; Knowledge management; Polynomials;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
  • Print_ISBN
    0-7803-7508-4
  • Type

    conf

  • DOI
    10.1109/ICMLC.2002.1175395
  • Filename
    1175395