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@article{147712,
        author = {Aabhas Solanki and Amit Kumar Sariya},
        title = {A CRITICAL REVIEW OF VARIOUS METHODOLOGIES FOR MINING HIGH UTILITY ITEM SETS FROM A UTILITY DATA SET},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {5},
        number = {10},
        pages = {319-321},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=147712},
        abstract = {Data Mining, also called knowledge Discovery in Database, is one of the latest research area, which has emerged in response to the Tsunami data or the flood of data, world is facing nowadays.  It has taken up the   challenge to develop techniques that can help humans to discover useful patterns	in massive data. One such important technique  is  utility  mining. Frequent item set mining works to discover  item set which are frequently appear in transaction database, which can be discover on the basis of support and confidence value of different itemset. Using frequent itemset mining concept as a base, many researchers have also proposed different new concept on utility based mining of itemset. This paper presents an analysis of various methodologies used for mining high utility item sets from a utility data set.},
        keywords = {Data Mining, High Utility Mining, Minimum Utility,  2 phase algorithm},
        month = {},
        }