IJMTES – MINING FREQUENT ITEMSET WITHOUT CANDIDATE GENERATION

Journal Title : International Journal of Modern Trends in Engineering and Science

Paper Title : MINING FREQUENT ITEMSET WITHOUT CANDIDATE GENERATION

Author’s Name : V Sangavi | P Divya
unnamed

Volume 04 Issue 03 2017

ISSN no:  2348-3121

Page no: 236-238

Abstract –Frequent item set mining is another advancement of information mining innovation. Among utility mining issues, utility mining with the item set offer system is a hard one as no against monotonicity property holds with the interestingness measure. High utility mining is not scalable and efficient with large database. In existing system it has two stage approach, in first phase it finds candidates of high utility pattern and in other phase it scan the raw data once again to identify the high utility pattern from the candidate. In proposed system it has one phase which scans the raw data directly to identify the high utility mining. Apriori algorithm is used to find pair product purchase and High utility item set with negative item value algorithm is efficient for large database.

Keywords – Frequent Item Set, Apriori Algorithm, High Utility Mining

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