基于协同过滤算法的服装个性化推荐研究  

Clothing Recommendation Research Based on Collaborative Filtering Algorithm

作　　者：蒋文娟[1] 苏佳 陆娜[1] 李富芸[1] JIANG Wen-juan;SU Jia;LU Na;LI Fu-yun(School of Information Science and Technology,Hainan Normal University,Haikou 571158,China)

机构地区：[1]海南师范大学信息科学技术学院

出　　处：《电脑知识与技术》2019年第12Z期194-196,共3页Computer Knowledge and Technology

基　　金：海南省自然科学基金项目(617119);海南省自然科学基金(617124);国家自然科学基金项目(61562023);海南省高等学校科学研究项目(Hnky2017-17)

摘　　要：个性化推荐系统可以帮助电子商务网站为用户提供快速有效的商品搜索服务,满足用户的需求,提高用户的购物效率。服装是电子商务平台的重要类目,但是由于用户对服装的偏好因素多,且用户对服装商品同时有趋同性和求异性,对服装个性化推荐的研究有很有必要。基于协同过滤算法,对用户收藏夹的信息进行了分析,计算出相似度最高的用户,并将该用户的收藏夹信息中目标用户还未关注到的信息推荐给目标用户,实现了一个简单电子商务网站的个性化推荐系统。Personalized recommendation system can help e-commerce websites to provide users with fast and effective product search services,meet users'needs,and improve users'shopping efficiency.Clothing is an important category of e-commerce platform,but due to the user's preference for clothing,and the user has the same and different tendency for clothing products at the same time,it is neces⁃sary to study the personalized recommendation of clothing.Based on the collaborative filtering algorithm,this paper the user's favorite information is analyzed,the users with the highest similarity are found out,and the information that the target user hasn't paid attention to but that is in the user's favorite information are recommended to the target user.A simple e-commerce website personalized recom⁃mendation system is implemented.

关 键 词：协同过滤 个性化推荐 推荐算法 相似度 电子商务 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]