Personalized recommendation method of marketing information of e-commerce platform based on user portrait
Due to the lack of pertinence of marketing information of existing e-commerce platforms,a personalized recommendation method of marketing information of e-commerce platform based on user portrait is designed.First,fully collect marketing information,user portrait personalized annotation,capture user interest and behavior mode.Then personalized constraints are set to ensure that the recommendations meet user needs and platform policies.Finally,the recommendation model is constructed to achieve accurate matching through the advanced algorithm.Experiments show that the average coverage of this method is up to 0.86,and the personalized recommendation quality and stability are good.
user portraite-commerce platformmarketing informationpersonalized recommendationcrawler tool
NETL
NSTL
万方数据
