Paper Details: Downloads: 473
Serial Number: P1120529001
Title: Association Rule Algorithm Based on Bitmap and Granular Computing
Authors: HONG-ZHEN ZHENG and DIAN-HUI CHU and DE-CHEN ZHAN
Abstract: It presents an association rule algorithm based on granular computing that doesn’t follow the generation-and-test strategy of Apriori algorithm It adopts the divide and conquers strategy, thus avoids the time consuming table scan to find and prune the itemsets. It is the fast bit operations based on its corresponding granular for all the operations of finding large itemsets from the datasets. The experimental result of the algorithm with Apriori, AprioriTid and Apriori Hybrid algorithms shows Bit- Association Rule is 2 to 3 orders of magnitudes faster. Our research indicates that bitmap and granular computing can greatly improve the performance of association rule algorithm, and are very promising for data mining applications.
Keywords: Data mining; Association rules; Bitmap.
Journal/Conference: International Journal of Artificial Intelligence and Machine Learning
Volume: 5
Issue: 3
Submission Date: 7/1/2005 12:00:00 AM
Review Date: 8/1/2005 12:00:00 AM
Publishing Date: 9/1/2005 12:00:00 AM
Article Downloads: 473
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