Collaborative Filtering Recommendation Algorithm Based on User Acceptable Rating Radius

Yue Huang (), Xuedong Gao () and Shujuan Gu ()
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Yue Huang: University of Science and Technology Beijing
Xuedong Gao: University of Science and Technology Beijing
Shujuan Gu: University of Science and Technology Beijing

A chapter in LISS 2013, 2015, pp 141-146 from Springer

Abstract: Abstract Collaborative Filtering (CF) is the most widely applied technique in recommender systems. The key of CF algorithms lies in user similarity calculation. When calculating similarity of two users, traditional CF algorithms put a high value on absolute ratings of common rated items while ignoring the relative rating level difference to the same items. To obtain more precise user preference of different users, a CF-based recommendation algorithm based on user acceptable rating radius is proposed. Experimental results of recommendation on four MovieLens data sets with different scales demonstrate that our method distinguishes users effectively and outperforms traditional methods with respect to recommendation accuracy.

Keywords: Collaborative filtering (CF); Recommender system; User similarity; User acceptable rating radius (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-40660-7_20

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DOI: 10.1007/978-3-642-40660-7_20

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