用户多兴趣下的个性化推荐算法分析  

Analysis of Personalized Recommendation Algorithms under Multi-user Interest

作　　者：邓磊[1] 古发辉[1] 李海平 Deng Lei;Gu Fahui;Li Haiping(Jiangxi College of Applied Technology,Ganzhou Jiangxi 341000,China)

机构地区：[1]江西应用技术职业学院,江西赣州341000

出　　处：《信息与电脑》2019年第3期69-71,共3页Information & Computer

摘　　要：目前,客户关系管理的一项重要内容为电子的商务个性化推荐。协同过滤算法是运用范围最广的推荐技术,但传统协同过滤推荐算法不适合多兴趣用户的推荐,则在此基础上通过协同过滤、项目协同过滤算法等,计算目标项目相似集,并在目标相似集中运用协同过滤算法处理。基于此,剖析用户多兴趣下的个性化推荐算法,并结合用户多需求的特点,总结个性推荐算法的优势,旨在通过完善算法推荐,实现个性化推荐算法与传统算法的融合,提高用户的体验满意度,充分展现个性化推荐算法的应用价值。At present,an important content of customer relationship management is personalized recommendation for e-commerce.Collaborative filtering algorithm is the most widely used recommendation technology,but the traditional collaborative filtering recommendation algorithm is not suitable for the recommendation of multi-interest users.On this basis,through collaborative filtering and project collaborative filtering algorithm,the similarity set of target items is calculated,and the collaborative filtering algorithm is used to process the similarity set of target items.Based on this,this paper analyses the personalized recommendation algorithm under multi-interest of users,and summarizes the advantages of personalized recommendation algorithm combined with the characteristics of multi-demand of users.The purpose is to achieve the integration of personalized recommendation algorithm and traditional algorithm by improving the algorithm recommendation,improve the user's experience satisfaction,and fully demonstrate the application value of personalized recommendation algorithm.

关 键 词：用户 多兴趣 个性化 推荐算法 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]