Efficient Algorithms for Mining the Concise and Lossless Representation of High Utility Itemsets
Abstract— Efficient Algorithms for Mining the Concise and Lossless Representation of High Utility Itemsets. Mining high utility itemsets (HUIs) from databases is an important data mining task, which refers to the discovery of itemsets with high utilities (e.g. high proﬁts). However, it may present too many HUIs to users, which also degrades the efﬁciency of the mining process. To achieve high efﬁciency for the mining task and provide a concise mining result to users, we propose a novel framework in this paper for mining closed þ high utility itemsets < Final Year Projects 2016 >, which serves as a compact and lossless representation of HUIs. We propose three efﬁcient algorithms named Apriori CH (Apriori-based algorithm for mining High utility Closed itemsets), Apriori HC-D (Apriori HC algorithm with Discarding unpromising and isolated items) and CHUD (Closed Þ þ High Utility Itemset Discovery) to ﬁnd this representation.
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