DocumentCode
3322376
Title
Mining Fuzzy Weighted Association Rules
Author
Olson, David L. ; Li, Yanhong
Author_Institution
Dept. of Manage., Nebraska Univ., Lincoln, NE
fYear
2007
fDate
Jan. 2007
Firstpage
53
Lastpage
53
Abstract
The paper combines and extends the technologies of fuzzy sets and association rules, considering users´ differential emphasis on each attribute through fuzzy regions. A fuzzy data mining algorithm is proposed to discovery fuzzy association rules for weighted quantitative data. This is expected to be more realistic and practical than crisp association rules. Discovered rules are expressed in natural language that is more understandable to humans. The paper demonstrates the performance of the proposed approach using a synthetic but realistic dataset
Keywords
data mining; fuzzy set theory; natural languages; very large databases; data mining; fuzzy set; fuzzy weighted association rule mining; natural language; rule discovery; Association rules; Dairy products; Data mining; Databases; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Humans; Itemsets; Natural languages;
fLanguage
English
Publisher
ieee
Conference_Titel
System Sciences, 2007. HICSS 2007. 40th Annual Hawaii International Conference on
Conference_Location
Waikoloa, HI
ISSN
1530-1605
Electronic_ISBN
1530-1605
Type
conf
DOI
10.1109/HICSS.2007.341
Filename
4076477
Link To Document