ESW-FI: An Improved Analysis of Frequent Itemsets Mining
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2012, Vol 1, Issue 5
Abstract
Frequent itemsets mining play an essential role in many datamining tasks. The frequent itemset mining over data streams is to find an approximate set of frequent itemsets in transaction with respect to a given support and threshold. It should support the flexible trade-off between processing time and mining accuracy. It should be time efficient even when the user-specified minimum support threshold is small. The objective was to propose an effective algorithm which generates frequent patterns in a very less time. Our approach has been developed based on improvement and analysis of MFI algorithm. In this paper, we introduce a new algorithm ESW-FI, to maintain a dynamically selected set of item sets over a sliding window. We keep some advantages of the previous approach and resolve the drawbacks, and produce the improved runtime and memory consumption. The proposed algorithm gave a guarantee of the output quality and also a bound on the memory usage.
Authors and Affiliations
K Jothimani , Dr Antony SelvadossThanamaniis
Keywords
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