DocumentCode
2370086
Title
Integrating fuzziness into OLAP for multidimensional fuzzy association rules mining
Author
Alhajj, Reda ; Kaya, Mehmet
Author_Institution
Dept. of Comput. Sci., Calgary Univ., Alta., Canada
fYear
2003
fDate
19-22 Nov. 2003
Firstpage
469
Lastpage
472
Abstract
We contribute to the ongoing research on multidimensional online association rules mining by proposing a general architecture that utilizes a fuzzy data cube for knowledge discovery. Three different methods are introduced to mine fuzzy association rules in the constructed fuzzy data cube, namely single dimension, multidimensional and hybrid association rules mining. Experimental results obtained for each of the three methods on the adult data of the United States census in 2000 show their effectiveness and applicability.
Keywords
data mining; data warehouses; fuzzy set theory; OLAP; fuzzy data cube; knowledge discovery; multidimensional fuzzy association rules mining; Association rules; Computer architecture; Computer science; Data engineering; Data mining; Databases; Fuzzy sets; Fuzzy systems; Knowledge engineering; Multidimensional systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining, 2003. ICDM 2003. Third IEEE International Conference on
Print_ISBN
0-7695-1978-4
Type
conf
DOI
10.1109/ICDM.2003.1250954
Filename
1250954
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