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Finding Frequent Pattern with Transaction and Occurrences based on Density Minimum Support Distribution

Author(s): Preeti Khare | Hitesh Gupta

Journal: International Journal of Advanced Computer Research
ISSN 2249-7277

Volume: 2;
Issue: 5;
Start page: 165;
Date: 2012;
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Keywords: Data Mining | Density wise Distribution | Minimum Support | Frequent Pattern

The importance of data mining is increasing exponentiallysince last decade and in recent time where there is verytough competition in the market where the quality ofinformation and information on time play a very crucialrole in decision making of policy has attracted a great dealof attention in the information industry and in society as awhole. In this approach we also use density minimumsupport so that we reduce the execution time. A frequentsuperset means it contains more transactions then theminimum support. It utilize the concept that if the item setis not frequent but the superset may be frequent which isconsider for the further data mining task. By thisapproach we can store the transaction on the daily basis,then we provide three different density zone based on thetransaction and minimum support which is low(L),Medium(M),High(H). Based on this approach wecategorize the item set for pruning. Our approach is basedon apriori algorithm but provides better reduction in timebecause of the prior separation in the data, which is usefulfor selecting according to the density wise distribution inIndia. Our algorithm provides the flexibility for improvedassociation and dynamic support. Comparative resultshows the effectiveness of our algorithm.
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