DocumentCode
1750934
Title
Linguistic association rules
Author
Roychowdhury, Shounak ; Pedrycz, Witold
Author_Institution
OracleCorporation, Redwood Shores, CA, USA
Volume
2
fYear
2001
fDate
25-28 July 2001
Firstpage
645
Abstract
The class of a priori algorithms are popular association rule mining techniques. However, these algorithms are computationally expensive. The authors propose another novel approach to extract association rules. The method represents an itemset information as a cell of a hypercube. The hypercube encodes associations between the items of each transaction. Apart from proposing the main result, we also propose linguistic association rules. Linguistic association rules encode fuzzy information and represent summarized rules
Keywords
associative processing; computational linguistics; data mining; fuzzy set theory; hypercube networks; very large databases; a priori algorithms; association rule extraction; association rule mining techniques; fuzzy information encoding; hypercube cell; itemset information; linguistic association rules; Association rules; Books; Data analysis; Data mining; Hypercubes; Itemsets; Pattern analysis; Profitability; Proposals; Web pages;
fLanguage
English
Publisher
ieee
Conference_Titel
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-7078-3
Type
conf
DOI
10.1109/NAFIPS.2001.944678
Filename
944678
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