Title :
Parallel algorithm for mining fuzzy association rules
Author :
Xu, Baowen ; Lu, Jianjiang ; Zhang, Yingzhou ; Xu, Lei ; Chen, Huowang ; Yang, Hongji
Author_Institution :
Dept. of Comput. Sci. & Eng., Southeast Univ. of Nanjing, China
Abstract :
The principle and steps of the algorithm for mining fuzzy association rules is studied, and the parallel algorithm for mining fuzzy association rules is presented. In this parallel mining algorithm, quantitative attributes are partitioned into several fuzzy sets by the parallel fuzzy c-means algorithm, and fuzzy sets are applied to soften the partition boundary of the attributes. Then, the parallel algorithm for mining Boolean association rules is improved to discover frequent fuzzy attributes. Last, the fuzzy association rules with at least fuzzy confidence are generated on all processors. The parallel mining algorithm is implemented on the distributed linked PC/workstation. The experiment results show that the parallel mining algorithm has fine scaleup, sizeup and speedup.
Keywords :
computer networks; data mining; fuzzy set theory; parallel algorithms; Boolean association; data mining; distributed linked PC; fuzzy association rules; fuzzy c-means algorithm; parallel algorithm; workstation; Association rules; Clustering algorithms; Computer science; Data mining; Educational technology; Fuzzy sets; Laboratories; Parallel algorithms; Partitioning algorithms; Relational databases;
Conference_Titel :
Cyberworlds, 2003. Proceedings. 2003 International Conference on
Print_ISBN :
0-7695-1922-9
DOI :
10.1109/CYBER.2003.1253467
