Recommender systems

Abstract

The ongoing rapid expansion of the Internet greatly increases the necessity of effective recommender systems for filtering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and practical achievements, unification and comparison of different approaches are lacking, which impedes further advances. In this article, we review recent developments in recommender systems and discuss the major challenges. We compare and evaluate available algorithms and examine their roles in the future developments. In addition to algorithms, physical aspects are described to illustrate macroscopic behavior of recommender systems. Potential impacts and future directions are discussed. We emphasize that recommendation has great scientific depth and combines diverse research fields which makes it interesting for physicists as well as interdisciplinary researchers.

Publication DOI: https://doi.org/10.1016/j.physrep.2012.02.006
Additional Information: © 2012, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: information filtering,networks,recommender systems,General Physics and Astronomy
Publication ISSN: 1873-6270
Last Modified: 29 Oct 2024 13:10
Date Deposited: 30 Nov 2015 11:20
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2012-10
Published Online Date: 2012-03-06
Authors: Lü, Linyuan
Medo, Matúš
Yeung, Chi Ho
Zhang, Yi-Cheng
Zhang, Zi-Ke
Zhou, Tao

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