Extending OLAP with fuzziness for effective mining of fuzzy multidimensional weighted association rules

Authors:
Mehmet Kaya;Reda Alhajj
Affiliations:
Dept. of Computer Eng, Firat University, Elazig, Turkey;Dept. of Computer Science, University of Calgary, Calgary, Alberta, Canada
Venue:
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Year:
2006

Citing 11
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Abstract

This paper contributes to the ongoing research on multidimensional online association rules mining by proposing a general architecture that utilizes a fuzzy data cube combined with the concepts of weight and multiple-level to mine fuzzy weighted multi-cross-level association rules. We compared the proposed approach to an existing approach that does not utilize fuzziness. Experimental results on the adult data of the United States census in year 2000 demonstrate the effectiveness and applicability of the proposed fuzzy OLAP based mining approach.