A framework for diversifying recommendation lists by user interest expansion

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 互联网大数据与安全信息学研究中心

	A framework for diversifying recommendation lists by user interest expansion
	Zhang, Zhu 1; Zheng, Xiaolong1 ; Zeng, Daniel Dajun1,2
刊名	KNOWLEDGE-BASED SYSTEMS
	2016-08-01
卷号	105 页码:83-95
关键词	Recommender systems Collaborative filtering Diversity Interest expansion Social tagging system
英文摘要	Recommender systems have been widely used to discover users' preferences and recommend interesting items to users during this age of information overload. Researchers in the field of recommender systems have realized that the quality of a top-N recommendation list involves not only relevance but also diversity. Most traditional recommendation algorithms are difficult to generate a diverse item list that can cover most of his/her interests for each user, since they mainly focus on predicting accurate items similar to the dominant interests of users. Additionally, they seldom exploit semantic information such as item tags and users' interest labels to improve recommendation diversity. In this paper, we propose a novel recommendation framework which mainly adopts an expansion strategy of user interests based on social tagging information. The framework enhances the diversity of users' preferences by expanding the sizes and categories of the original user-item interaction records, and then adopts traditional recommendation models to generate recommendation lists. Empirical evaluations on three real-world data sets show that our method can effectively improve the accuracy and diversity of item recommendation. (C) 2016 Elsevier B.V. All rights reserved.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Computer Science, Artificial Intelligence
研究领域[WOS]	Computer Science
关键词[WOS]	SYSTEMS ; TAG
收录类别	SCI
语种	英语
WOS记录号	WOS:000378961200008
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/12149]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_互联网大数据与安全信息学研究中心
作者单位	1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Univ Arizona, Dept Management Informat Syst, Tucson, AZ 85721 USA
推荐引用方式 GB/T 7714	Zhang, Zhu,Zheng, Xiaolong,Zeng, Daniel Dajun. A framework for diversifying recommendation lists by user interest expansion[J]. KNOWLEDGE-BASED SYSTEMS,2016,105:83-95.
APA	Zhang, Zhu,Zheng, Xiaolong,&Zeng, Daniel Dajun.(2016).A framework for diversifying recommendation lists by user interest expansion.KNOWLEDGE-BASED SYSTEMS,105,83-95.
MLA	Zhang, Zhu,et al."A framework for diversifying recommendation lists by user interest expansion".KNOWLEDGE-BASED SYSTEMS 105(2016):83-95.