基于用户行为的个性化电商信息推送系统设计  

Design of Personalized E-Commerce Information Push System Based on User Behavior

作　　者：殷常涛 王一凡 YIN Changtao;WANG Yifan(Employment and Entrepreneurship Division,Sias University,Zhengzhou Henan 451100,China;City University of Zhengzhou,Zhengzhou Henan 452370,China)

机构地区：[1]郑州西亚斯学院就业创业处,河南郑州451100 [2]郑州城市职业学院,河南郑州452370

出　　处：《信息与电脑》2022年第18期106-108,共3页Information & Computer

基　　金：郑州西亚斯学院2021年度应用型本科高校建设专项教改基金资助项目(项目编号:+2021YYXZX10)。

摘　　要：为提高推荐产品与用户需求产品的适配度,基于用户行为分析设计了一种针对电子商务的个性化信息推荐系统。首先,使用网络爬虫技术检索电子商务平台的运行终端,获取电商用户行为信息;其次,构建电商用户行为信息表,分析获取的用户行为数据,通过用户对产品需求来计算用户的偏好度;最后,引进关联规则,挖掘符合用户喜好的产品,实现个性化信息主动推送服务。实验证明,该系统推荐的商品与用户需求产品两者适配度在90%以上,且系统推送后,显著提升了用户在电商平台的点击次数与浏览时间。In order to improve the adaptability of recommended products to users’ needs,this paper designs a personalized information recommendation system for e-commerce based on user behavior analysis.Firstly,use Web crawler technology to retrieve the operation terminal of e-commerce platform and obtain the behavior information of e-commerce users.Secondly,build the e-commerce user behavior information table,analyze the obtained user behavior data,and calculate the user preference through the user’s demand for products.Finally,introduce association rules,mine products that meet user preferences,and realize personalized information active push service.Experiments show that the suitability of the products recommended by the system and the products required by users is more than 90%,and after the system is pushed,the number of clicks and browsing time of users on the e-commerce platform are significantly improved.

关 键 词：用户行为 关联规则 偏好度 推送系统 电商信息 个性化 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论]