Mining multi-cross-level fuzzy weighted association rules - Kaya, M; Alhajj, R (Ieee, 2004)
This paper proposes a novel approach for mining fuzzy weighted multi-cross-level association rules by simply integrating the advantages of several concepts, including fuzziness, cross-level mining, weighted mining and linguistic terms for minimum support, minimum confidence and item importance. Experimental results conducted on a synthetic database demonstrate the importance, effectiveness and applicability of the proposed approach.
2nd IEEE International Conference on Intelligent Systems -- JUN 22-24, 2004 -- Varna, BULGARIA
Keywords: association rules; data mining; fuzziness; linguistic terms; multi-cross-level rules; weighted rules