计算机技术与发展2018，Vol.28Issue(2)：83-87,5.DOI:10.3969/j.issn.1673-629X.2018.02.019
推荐系统冷启动问题解决策略研究
Research on Solution of Solving Cold Start Problem in Recommender Systems
摘要
Abstract
Recommendation systems apply machine learning techniques to filter and locate information accurately,and can predict whether a user would like a given resource.Traditional collaborative filtering systems have to deal with the cold-start problems as new users and items are always present,which fail to produce the accurate recommendation for users.In this paper we first illustrate the causes and the signifi-cances of solving the cold-start problems according to the current achievements in research,and then summarize the existing algorithms and compare the performance of them.Finally,we try to give the difficulties and future directions of recommender system.It was found that the most popular way is to have mixed data sources and algorithms to improve the accuracy and efficiency of recommender system at present,but there still have been some difficulty like how to protect personal privacy during getting users' information or how to establish the perform-ance evaluation of recommendation systems.关键词
推荐系统/协同过滤/用户冷启动/项目冷启动/解决策略Key words
recommender system/collaborative filtering/new-user cold-start/new-item cold-start/solving methods分类
信息技术与安全科学引用本文复制引用
乔雨,李玲娟..推荐系统冷启动问题解决策略研究[J].计算机技术与发展,2018,28(2):83-87,5.基金项目
国家自然科学基金(61302158,61571238) （61302158,61571238）
