Exploring Social Relations for Personalized Tag Recommendation in Social Tagging Systems

doi:10.1587/transinf.E94.D.542

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	Exploring Social Relations for Personalized Tag Recommendation in Social Tagging Systems
	Liu, Kaipeng 1; Fang, Binxing 2; Zhang, Weizhe 1
刊名	IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
	2011-03-01
卷号	E94D 期号:3 页码:542-551
关键词	social tagging systems personalized tag recommendation social relations collaborative filtering
ISSN号	0916-8532
DOI	10.1587/transinf.E94.D.542
英文摘要	With the emergence of Web 2.0, social tagging systems become highly popular in recent years and thus form the so-called folksonomies. Personalized tag recommendation in social tagging systems is to provide a user with a ranked list of tags for a specific resource that best serves the user's needs. Many existing tag recommendation approaches assume that users are independent and identically distributed. This assumption ignores the social relations between users, which are increasingly popular nowadays. In this paper, we investigate the role of social relations in the task of tag recommendation and propose a personalized collaborative filtering algorithm. In addition to the social annotations made by collaborative users, we inject the social relations between users and the content similarities between resources into a graph representation of folksonomies. To fully explore the structure of this graph, instead of computing similarities between objects using feature vectors, we exploit the method of random-walk computation of similarities, which furthermore enable us to model a user's tag preferences with the similarities between the user and all the tags. We combine both the collaborative information and the tag preferences to recommend personalized tags to users. We conduct experiments on a dataset collected from a real-world system. The results of comparative experiments show that the proposed algorithm outperforms state-of-the-art tag recommendation algorithms in terms of prediction quality measured by precision, recall and NDCG.
WOS研究方向	Computer Science
语种	英语
出版者	IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
WOS记录号	WOS:000290125900017
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/13096]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhang, Weizhe
作者单位	1.Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150001, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Network Sci & Technol, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Liu, Kaipeng,Fang, Binxing,Zhang, Weizhe. Exploring Social Relations for Personalized Tag Recommendation in Social Tagging Systems[J]. IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS,2011,E94D(3):542-551.
APA	Liu, Kaipeng,Fang, Binxing,&Zhang, Weizhe.(2011).Exploring Social Relations for Personalized Tag Recommendation in Social Tagging Systems.IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS,E94D(3),542-551.
MLA	Liu, Kaipeng,et al."Exploring Social Relations for Personalized Tag Recommendation in Social Tagging Systems".IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS E94D.3(2011):542-551.