Collaborative Filtering Algorithms Based on Kendall Correlation in Recommender Systems

In this work, Kendall correlation based collaborative filtering algorithms for the recommender systems are proposed. The Kendall correlation method is used to measure the correlation amongst users by means of considering the relative order of the users＇ ratings. Kendall based algorithm is based upon...

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Bibliographic Details
Published in:Wuhan University journal of natural sciences 2006-09, Vol.11 (5), p.1086-1090
Main Authors: Yu, Yao, Shanfeng, Zhu, Xinmeng, Chen
Format: Article
Language:English
Subjects:
协作滤除算法
新委任系统
正相关
肯德尔相关
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Summary:In this work, Kendall correlation based collaborative filtering algorithms for the recommender systems are proposed. The Kendall correlation method is used to measure the correlation amongst users by means of considering the relative order of the users＇ ratings. Kendall based algorithm is based upon a more general model and thus could be more widely applied in e-commerce. Another discovery of this work is that the consideration of only positive correlated neighbors in prediction, in both Pearson and Kendall algorithms, achieves higher accuracy than the consideration of all neighbors, with only a small loss of coverage.
ISSN:1007-1202
1993-4998
DOI:10.1007/BF02829215