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	Recommending scientific literatures in a collaborative tagging environment
	Yin, Ping ; Zhang, Ming ; Li, Xiaoming
	2007
关键词	SYSTEMS
英文摘要	Recently, collaborative tagging has become popular in the web2.0 world. Tags can be helpful if used for the recommendation since they reflect characteristic content features of the resources. However, there are few researches which introduce tags into the recommendation. This paper proposes a tag-based recommendation framework for scientific literatures which models the user interests with tags and literature keywords. A hybrid recommendation algorithm is then applied which is similar to the user-user collaborative filtering algorithm except that the user similarity is measured based on the vector model of user keywords other than the rating matrix, and that the rating is not from the user but represented as user-item similarity computed with the dot-product-based similarity instead of the cosine-based similarity. Experiments show that our tag-based algorithm is better than the baseline algorithm and the extension of user model and dot-product-based similarity computation are also helpful.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000252143400060&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Computer Science, Hardware & Architecture; Computer Science, Information Systems; Computer Science, Theory & Methods; Information Science & Library Science; EI; CPCI-S(ISTP); CPCI-SSH(ISSHP); 1
语种	英语
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/293303]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Yin, Ping,Zhang, Ming,Li, Xiaoming. Recommending scientific literatures in a collaborative tagging environment. 2007-01-01.

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