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FUFM-High Utility Itemsets in Transactional Database

Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.3, No. 3)

Publication Date:

Authors : ;

Page : 889-893

Keywords : Candidate pruning; frequent itemset; high utility itemset; utility mining; data mining;

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Abstract

The practical usefulness of the frequent item set mining is limited by the significance of the discovered itemsets. There are two principal limitations. A huge number of frequent item sets that are not interesting to the user are often generate when the minimum support is low.Proposing two algorithms, namely utility pattern growth (UP-Growth) and UP-Growth+, for mining high utility itemsets with a set of effective strategies for pruning candidate itemsets.

Last modified: 2014-03-29 21:07:08