协同过滤推荐算法研究进展  

Research process of collaborative filtering recommendation algorithm

作　　者：翁小兰[1,2] 王志坚[1] 

机构地区：[1]河海大学计算机与信息学院,南京211100 [2]淮阴师范学院计算机科学与技术学院,江苏淮安223300

出　　处：《计算机工程与应用》2018年第1期25-31,共7页Computer Engineering and Applications

基　　金：国家自然科学基金青年基金(No.11201168)

摘　　要：推荐技术在各个领域得到了广泛的应用,其中协同过滤推荐算法显得尤为突出。从基本概念、工作流程以及评估指标等方面介绍了传统的协同过滤推荐算法,对此类算法存在的数据稀疏性、冷启动、扩展性问题进行了分析,并分类详细归纳了这些问题的研究现状和解决方案;最后提出了协同过滤推荐算法在融合大数据技术、社会网络分析技术以及关键用户分析技术三方面的研究热点。Recommended technology is widely applied in various fields, and the successful application of the collaborative filtering recommendation algorithm is especially significant. This paper mainly introduces the basic concept and principle of the collaborative filtering recommendation algorithm, including such aspects: algorithm work flow, recommends process as well as the experiment assessment. The collaborative filtering technique faces up to some problem, although it has achieved great success, because of its algorithm features. The paper analyzes these problems and proposes the corresponding solution of collaborative filtering recommendation algorithm, and finally puts forward the new research hotspots of the collaborative filtering recommendation algorithm.

关 键 词：协同过滤 冷启动 稀疏性 扩展性 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]