基于多视图深度学习的推荐系统跨域用户建模算法  

Cross Domain User Modeling Algorithm of Recommender System Based on Multi-view Deep Learning

作　　者：刘凯[1] LIU Kai(Center of Network Information,Ningxia Medical University,Yinchuan,750001,Ningxia)

机构地区：[1]宁夏医科大学网络信息中心,宁夏银川750001

出　　处：《蚌埠学院学报》2021年第2期79-83,共5页Journal of Bengbu University

基　　金：宁夏医科大学教育教学改革研究项目(NYJY1829)。

摘　　要：在线服务在很大程度上依赖于推荐系统智能化地向用户推荐有效内容,针对这一现状,参考可视化深度学习方法,基于内容推荐系统来建立用户模型,将用户和项目的数据信息映射到高维空间中,使得用户数据首选项之间的相似性达到最大,以满足推荐系统的推荐质量和内容的可扩展性。At present,online service largely relies on that recommendation system to intelligently recommend effective content to users.In view of this situation,it used the visual deep learning method in this paper to build the user model based on the content recommendation system,and maped the data information of users and projects into the high-dimensional space,so as to maximize the similarity between the preferences of user data,and meet the recommendation quality and content capability of the recommendation system.

关 键 词：用户建模 推荐系统 多视图学习 深度学习 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TP183[自动化与计算机技术—计算机科学与技术]