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	A collaborative filtering recommendation system by unifying user similarity and item similarity
	Zhang, Dongzhan ; Xu, Chao ; Zhang DZ(张东站)
	2012
关键词	Information management Rating Social networking (online)
英文摘要	Conference Name:Int. Workshops on Web-Age Information Management, WAIM 2011: 1st Int. Workshop on Web-Based Geographic Information Management, WGIM 2011, 3rd Int. Workshop on XML Data Management, XMLDM 2011, 1st Int. Workshop on Social Network Analysis, SNA 2011. Conference Address: Wuhan, China. Time:September 14, 2011 - September 16, 2011.; Collaborative filtering recommendation system based on user similarity has been wildly studied because of its broad application. In reality, users keep partial similarity with larger possibility. Computing the whole similarity between users without considering item category is inaccurate when predicting rating for a special category of items by using collaborative filtering recommendation system. Aiming at this problem, a new similarity measurement was given. Based on the new similarity measurement, a new collaborative filtering algorithm named UICF was presented for recommendation. When predicting rating for the special item, UICF chooses the users as nearest neighbors which have the similar rating feature for the items with the same type of the special item, instead of for all the items. Experimental results show the higher quality of the algorithm. 漏 2012 Springer-Verlag.
语种	英语
出处	http://dx.doi.org/10.1007/978-3-642-28635-3_17
出版者	Springer Verlag
内容类型	其他
源URL	[http://dspace.xmu.edu.cn/handle/2288/86702]
专题	信息技术－会议论文
推荐引用方式 GB/T 7714	Zhang, Dongzhan,Xu, Chao,Zhang DZ. A collaborative filtering recommendation system by unifying user similarity and item similarity. 2012-01-01.

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