期刊
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
卷 458, 期 -, 页码 364-377出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.physa.2016.04.025
关键词
Recommender system; Collaborative ranking; Signed network; Similarity measure; Preference data; Personalized ranking
Collaborative ranking is an emerging field of recommender systems that utilizes users' preference data rather than rating values. Unfortunately, neighbor-based collaborative ranking has gained little attention despite its more flexibility and justifiability. This paper proposes a novel framework, called SibRank that seeks to improve the state of the art neighbor-based collaborative ranking methods. SibRank represents users' preferences as a signed bipartite network, and finds similar users, through a novel personalized ranking algorithm in signed networks. (C) 2016 Elsevier B.V. All rights reserved.
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