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Apriori algorithm is one of the most effective algorithms for mining frequent itemsets of Boolean Association rules. Decision tree is a method to analyze and summarize the attributes of a large number of samples. The frequent itemsets are used to generate the association rules, and the strong association rules are generated according to the minimum confidence set by the user. The paper presents research on novel model of data mining based on improved association rules and clustering algorithm. Finally, the effectiveness of the proposed algorithm is verified by experiments.

Research On Novel Model of Data Mining Based on Improved Association Rules and Clustering Algorithm