Data Mining is an activity that extracts some new useful information contained in large databases. Traditional data mining methodologies focused largely on detecting the statistical correlations between the items that are more frequent in the transaction databases. Association Rule Mining focuses on existence of an item in a transaction, whether or not it is purchased. The drawbacks of frequent itemset mining leads to consider a utility mining, which allows a user to conveniently express the

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... fulness of itemsets as utility values and then find itemsets with high utility values. In practice the utility value of an itemset can be profit, popularity, or some other measures of user's preference. There exist several algorithms in literature to mine high utility itemsets. In this paper, a literature survey of various high utility itemset mining algorithms has been presented. This record was migrated from the OpenDepot repository service in June, 2017 before shutting down.