DocumentCode :
3018939
Title :
Generalized Association Rule and Orexis Degree
Author :
Peiyou, Han
Author_Institution :
Coll. of Comput. Sci. & Inf. Eng., Zhejiang Gongshang Univ., Hangzhou, China
fYear :
2010
fDate :
25-27 June 2010
Firstpage :
3784
Lastpage :
3787
Abstract :
Through import generalized fuzzy sets in data mining, use generalized fuzzy sets, support and confidence of association rules, put forward the concept left support, right support and orexis degree, give generalized association rules, improve Apriori algorithm, and then under generalized association rules orexis-based, not only can able to mine positive true association rules, but also negative false association rules, and then association rules and Apriori algorithm are the same with area and purpose widely.
Keywords :
data mining; fuzzy set theory; Apriori algorithm; Orexis degree; data mining; generalized association rule; generalized fuzzy sets; Association rules; Fuzzy sets; Servers; Software; Software algorithms; Strontium; association rules; data mining; generalized fuzzy sets; orexis degree;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Control Engineering (ICECE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6880-5
Type :
conf
DOI :
10.1109/iCECE.2010.923
Filename :
5631873
Link To Document :
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