Research And Implementation Of Personalized Recommendation Algorithm On WeChat E-commerce Platform

With the rapid development of e-commerce,the competition among e-commerce platforms is increasingly fierce.How to stand out among many e-commerce platforms has become crucial.The Wechat Official Account launched by WeChat in 2012 enables businesses and users to communicate and interact with each other in text,voice and other ways,thus forming a marketing mode combining O2 O.This marketing model has brought new vitality to e-commerce,and businesses have invested in this new marketing model to improve economic benefits.Personalized recommendation technology is a tool that can improve the sales profits of e-commerce platforms.It is widely used in e-commerce.Large e-commerce platforms at home and abroad all use personalized recommendation technology to improve user stickiness and retention.This paper relies on a company to organize eco-tourism activities and its merchandise sales,through the research on personalized recommendation algorithm,combined with the actual needs of the company,develops and designs a WeChat e-commerce platform based on the combined sales mode of O2 O and realizes personalized recommendation of merchandise.Firstly,this paper studies collaborative filtering recommendation algorithm,analyzes the advantages and disadvantages of user-based collaborative filtering algorithm(UserCF)and item-based collaborative filtering algorithm(ItemCF),and designs a weighted hybrid recommendation algorithm based on score matrix pre-filling to solve the problem of data sparsity.In this algorithm,ItemCF is improved by narrowing the scope of finding the nearest neighbor,then the user-item scoring matrix is prefilled with the user scoring average and the item scoring average,and finally the recommendation results are generated by weighting the UserCF and the improved ItemCF.The experimental results show that the hybrid algorithm can effectively improve the accuracy of recommendation results.Secondly,this paper proposes the overall design of WeChat e-commerce platform based on MVC design idea in combination with project demand analysis.This paper analyzes and designs the system architecture,functional modules and databases,and realizes the O2 O sales mode of e-commerce platform through Wechat Official Account and WeChat applet,and tests the system,and complete the construction of WeChat e-commerce platform that includescommodity recommendation function and integrates online to offline and C2 C modes.Finally,the main work of this paper is summarized,and the shortcomings of the platform and the next improvement direction are put forward.The WeChat e-commerce designed and developed in this paper realizes the basic functions of the e-commerce platform,and realizes the use of the weighted hybrid recommendation algorithm based on the pre-filling of the scoring matrix to recommend the products for the user and achieves the design goal.