Coarse cluster enhancing collaborative recommendation for social network systems

doi:10.1016/j.physa.2017.04.131

	Coarse cluster enhancing collaborative recommendation for social network systems
	Zhao, Yao-Dong 1,2; Cai, Shi-Min 1,2; Tang, Ming 1,2; Shang, Min-Sheng 2,3
刊名	PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
	2017-10-01
卷号	483 页码:209-218
关键词	Recommender system Social network system Social tagging system Tripartite graph Time complexity Collaborative user model
ISSN号	0378-4371
DOI	10.1016/j.physa.2017.04.131
通讯作者	Cai, SM (reprint author), Univ Elect Sci & Technol China, Sch Comp Sci & Engn, Web Sci Ctr, Chengdu 610073, Peoples R China.
英文摘要	Traditional collaborative filtering based recommender systems for social network systems bring very high demands on time complexity due to computing similarities of all pairs of users via resource usages and annotation actions, which thus strongly suppresses recommending speed. In this paper, to overcome this drawback, we propose a novel approach, namely coarse cluster that partitions similar users and associated items at a high speed to enhance user-based collaborative filtering, and then develop a fast collaborative user model for the social tagging systems. The experimental results based on Delicious dataset show that the proposed model is able to dramatically reduce the processing time cost greater than 90% and relatively improve the accuracy in comparison with the ordinary user-based collaborative filtering, and is robust for the initial parameter. Most importantly, the proposed model can be conveniently extended by introducing more users' information (e.g., profiles) and practically applied for the large-scale social network systems to enhance the recommending speed without accuracy loss. (C) 2017 Elsevier B.V. All rights reserved.
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资助项目	National Natural Science Foundation of China[61673086] ; National Natural Science Foundation of China[91646114] ; National Natural Science Foundation of China[11575041] ; National Natural Science Foundation of China[61433014] ; National Natural Science Foundation of China[61370150] ; Fundamental Research Funds of the Central Universities[ZYGX2015J153] ; Shanghai Research Institute of Publishing and Media[SAYB1402]
WOS研究方向	Physics
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000405062000021
内容类型	期刊论文
源URL	[http://172.16.51.4:88/handle/2HOD01W0/150]
专题	中国科学院重庆绿色智能技术研究院
通讯作者	Cai, Shi-Min
作者单位	1.Univ Elect Sci & Technol China, Sch Comp Sci & Engn, Web Sci Ctr, Chengdu 610073, Peoples R China 2.Univ Elect Sci & Technol China, Big Data Res Ctr, Chengdu 610073, Peoples R China 3.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Yao-Dong,Cai, Shi-Min,Tang, Ming,et al. Coarse cluster enhancing collaborative recommendation for social network systems[J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS,2017,483:209-218.
APA	Zhao, Yao-Dong,Cai, Shi-Min,Tang, Ming,&Shang, Min-Sheng.(2017).Coarse cluster enhancing collaborative recommendation for social network systems.PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS,483,209-218.
MLA	Zhao, Yao-Dong,et al."Coarse cluster enhancing collaborative recommendation for social network systems".PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 483(2017):209-218.