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
Link To Document :
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