A Modified Apriori Algorithm For Fast And Accurate Generation Of Frequent Item Sets
Journal: International Journal of Scientific & Technology Research (Vol.6, No. 8)Publication Date: 2017-08-15
Authors : K.A.Baffour; C.Osei-Bonsu; A.F. Adekoya;
Page : 169-173
Keywords : Association Rule Mining; Candidate itemsets; Combinations; Database; Frequent itemsets; Join; Prune.;
Abstract
The Classical Apriori Algorithm CAA which is used for finding frequent itemsets in Association Rule Mining consists of two main steps the join step for generating candidate itemsets and the prune step for eliminating candidate itemsets that are not frequent.The CAA despite its simplicity has several limitations the generation of a large number of candidate itemsets the generation of many combinations that never occur in the database as well as the need to perform several full database scans when generating frequent itemsets. In this research a Modified Apriori Algorithm MAA is proposed. The MAA succeeded in eliminating a major problem of the CAA by using a technique where combinations are generated on row basis.A comparison of the results of the proposed algorithm against the Classical Apriori Algorithm shows that the proposed algorithm is faster and more efficient. The MAA was implemented on suitable databases and the results were compared against results from our 4 other Improved Apriori Algorithms for efficiency. The results of the comparative analysis showed that the MAA was more efficient in terms of execution time than the other Improved Apriori Algorithm.
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Last modified: 2017-10-22 19:56:52