Research on Application of Improved Association Rules Mining Algorithm in Personalized Recommendation

Abstract

Abstract Traditional association rule mining does not consider the importance of each item, so the actual process lacks certain pertinence. Based on the New-Apriori algorithm and the Fp-growth algorithm idea, this paper proposes an improved association rule algorithm based on Fp-tree, Constructs the general process of personalized recommendation of association rules. And uses the Web log file to use the frequency of web pages being selected by users as the weight value, and realizes the algorithm of the personalized recommendation system. The experimental results show that the algorithm has high accuracy and effectiveness.