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FPC+: Algorithm for Mining of Frequent Closed Itemsets


Darshan Modi , Government Engineering College, Gandhinagar; Namrata Shroff, Government Engineering College, Gandhinagar


Data mining, frequent closed itemset mining, frequent closed itemsets, Association rules


In this paper, we presents a new algorithm for finding closed frequent item sets, which is an abridged and lossless demonstration of every frequent itemsets that able to mine from a transactional database. We used a divide-and-conquer method and follow a specific visiting and partitioning method of the search space found on a real theoretic framework, which describes the difficulty of closed itemsets mining in very much detailing. The algorithm takes some exaggeration targeted to minimize time in finding itemset supports and their closures. We propose a pruning technique using Lattice method and Linkage Disequilibrium method, which, dislike other past methods, does not demand the full set of closed patterns mined so long and to be hold in the main memory. This algorithm also passes every passed partition of the search space to be mined freely in any position and in parallel also. We present our new algorithm called FPC+ for frequent closed itemsets and compare it with existing approaches like Apriori, FP-Growth, Closet+ and BCTFI in this paper.

Other Details

Paper ID: IJSRDV4I90458
Published in: Volume : 4, Issue : 9
Publication Date: 01/12/2016
Page(s): 618-622

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