基于用户画像的电商平台营销信息个性化推荐方法
Personalized recommendation method of marketing information of e-commerce platform based on user portrait
王圆圆1
作者信息
- 1. 郑州科技学院,河南 郑州 450000
- 折叠
摘要
现有电商平台营销信息缺乏针对性,为此文章设计了一种基于用户画像的电商平台营销信息个性化推荐方法.首先全面采集营销信息,对用户画像进行个性化标注,捕捉用户兴趣和行为模式.然后设置个性化约束条件,确保推荐符合用户需求和平台的策略.最后构建推荐模型,通过先进的算法实现精准匹配.实验表明,该方法平均覆盖率高达0.86,个性化推荐质量与稳定性较好.
Abstract
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.
关键词
用户画像/电商平台/营销信息/个性化推荐/爬虫工具Key words
user portrait/e-commerce platform/marketing information/personalized recommendation/crawler tool引用本文复制引用
出版年
2024
NETL
NSTL
万方数据