A personalised recommendation algorithm for e-commerce network information based on two-dimensional correlation Online publication date: Mon, 05-Dec-2022
by Enwei Cao
International Journal of Autonomous and Adaptive Communications Systems (IJAACS), Vol. 15, No. 4, 2022
Abstract: In view of the poor accuracy and low efficiency of the traditional e-commerce personalised recommendation algorithm, a two-dimensional correlation-based personalised recommendation algorithm for e-commerce network information was proposed. Using two-dimensional correlation, categorise e-commerce user relevancy analysis to measure the personality interests of users in the electronic commerce network, e-commerce project through the Jaccard similarity coefficient, the similarity calculation between the interest spread model was constructed, differentiate the importance of data push grades, and numerical characteristics of e-commerce behaviour are influenced by the importance level, which is calculated by using the sorting result to realise e-commerce personalised recommendation. The experimental results show that the proposed method has high accuracy, diversity and efficiency.
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