Scalable parallel data mining for association rules
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Parallel mining algorithms for generalized association rules with classification hierarchy
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
SC '97 Proceedings of the 1997 ACM/IEEE conference on Supercomputing
Discovery of Multiple-Level Association Rules from Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Mining Generalized Association Rules
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
HiPC '01 Proceedings of the 8th International Conference on High Performance Computing
Parallel Data Mining on Large Scale PC Cluster
WAIM '00 Proceedings of the First International Conference on Web-Age Information Management
Parallel Image Matching on PC Cluster
Proceedings of the 8th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
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One of the most important problems in data mining is discovery of association rules in large database. We had proposed parallel algorithms for mining generalized association rules with classification hierarchy. In this paper, we implemented the proposed algorithms on a large scale PC cluster which consists of one hundred PCs interconnected by an ATM switch, and analyzed the performance of our algorithms using a large amount of transaction dataset. Performance evaluations show our parallel algorithms are effective for handling skew for such large scale parallel systems.