现代电子技术2016，Vol.39Issue(15)：133-136,4.DOI:10.16652/j.issn.1004-373x.2016.15.034
基于加权关联规则挖掘算法的电子商务商品推荐系统研究
Research on e-commerce commodity recommendation system based on mining algorithm of weighted association rules
郝海涛 1马元元2
作者信息
- 1. 中山市广播电视大学，广东 中山 528403
- 2. 中山职业技术学院 信息工程学院，广东 中山 528404
- 折叠
摘要
Abstract
To solve the direct commodity rapid and accurate matching problem between electronic shoppers and merchants, the e⁃commerce commodity recommendation system based on mining algorithm of weighted association rules is researched. Ai⁃ming at the insufficiency of the classic Apriori algorithm,a new weighted fuzzy association rules mining algorithm is put forward to ensure the downward closure of frequent item sets. The work flow of the recommendation system was tested through the struc⁃tural design of e⁃commerce recommendation system,data preprocessing module design and recommendation module design. The hit rate is selected as the evaluation standard of different recommendation models. The contrastive analysis for the practical col⁃lected data was conducted with the half⁃off cross test method. The experimental results show that the hit rate of Top⁃N products in association rule set is significantly higher than that of the interest recommendation method and best selling recommendation method.关键词
加权关联规则/挖掘算法/电子商务/推荐系统Key words
weighted association rule/mining algorithm/electronic commerce/recommendation system分类
信息技术与安全科学引用本文复制引用
郝海涛,马元元..基于加权关联规则挖掘算法的电子商务商品推荐系统研究[J].现代电子技术,2016,39(15):133-136,4.
