• DocumentCode
    1659012
  • Title

    Toward knowledge-driven spiral discovery of exception rules

  • Author

    Yamada, Yuu ; Suzuki, Einoshin

  • Author_Institution
    Div. of Electr. & Comput. Eng., Yokohama Nat. Univ., Japan
  • Volume
    2
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    872
  • Lastpage
    877
  • Abstract
    We report our preliminary endeavour for spiral discovery of exception rules based on discovered pieces of knowledge. An exception rule, which represents a deviational pattern to a general rule, exhibits unexpectedness and is sometimes extremely useful. We have proposed a domain-independent approach for simultaneous discovery of exception rules and their general rules. Exceptions are always interesting to discoverers, as they challenge the existing knowledge and often lead to the growth of knowledge in new directions. We propose a discovery method which exploits pre-discovered pairs of exception rules and their general rules, and apply it to a benchmark data set in knowledge discovery
  • Keywords
    data mining; knowledge based systems; data mining; domain independent approach; exception rule discovery; knowledge discovery; knowledge driven spiral discovery; rules discovery; Data mining; Knowledge engineering; Machine learning; Production; Spirals;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    0-7803-7280-8
  • Type

    conf

  • DOI
    10.1109/FUZZ.2002.1006619
  • Filename
    1006619