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
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