E-Commerce Product Recommendation Method Based on Collaborative Filtering Technology

This paper concentrates on the problem of E-commerce product recommendation, and E-commerce market has attracted more and more attentions. Collaborative filtering algorithm supposes that when two users have similar ratings on products, they may have similar preferences. To combine the user preference information and the collaborative filtering model together, we suppose that if there are two users who share the similar interest, it is very possible for them to select similar products. Afterwards, we design an E-commerce product recommendation algorithm based on collaborative filtering model to compute the recommendation score. Finally, experimental results prove that the proposed method can recommend more relevant products for users with high accuracy.