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A new algorithm, named SCan-MAX for mining distributed maximal frequent itemsets from databases was proposed, the SCan-MAX used Sorted SCan-tree to store all the information of the transactions from the databases. SCan-MAX firstly scanned the local database and then gets the global 1-frequent itemsets, and then it created the SCan-tree on each node and used orderly sequence to store frequent itemsets...
Mining association rules is an important issue in KDD applications. In this paper, we first use the cloud model to dynamically divide attribute value to overcome the shortcoming that the concept was partitioned by experience, and then explore the application of cloud models in mining association rules from credit card database by the improved Apriori algorithm. The result of experiment shows that...
Previous algorithms mine the complete set of sequential patterns in large database efficiently, but when mining long sequential patterns in dense databases or using low minimum supports, it may produce many redundant patterns and some uninterested patterns. In this paper, a novel weighted closed sequential pattern mining algorithm (WCSpan) is presented, which implements the closed sequential pattern...
Association rules mining is an important task in data mining and the normal measures support and confidence are useful for finding association rules between the items. However, the process of finding frequent items would prune infrequent items which may include some useful relationships of association patterns. The new measures comsup, comcof and comsup' are proposed to resolve this problem effectively...
Applying association rule mining to power demand-side management can supply references to optimizing decision-making program by power-supply companies. We introduce the principle of advancing power demand-side management measure accepted by user using association rules, and discuss the feasibility of choosing load-adjusting electric-power terminal based on multi-dimensional association rule mining...
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