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Recommender systems

期刊

出版社

ELSEVIER
DOI: 10.1016/j.physrep.2012.02.006

关键词

Recommender systems; Information filtering; Networks

资金

  1. EU FET-Open Grant [231200]
  2. National Natural Science Foundation of China [11075031, 11105024, 61103109, 60973069]
  3. EU FET FP7 project STAMINA [FP7-265496]
  4. Research Funds for the Central Universities (UESTC)

向作者/读者索取更多资源

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. (c) 2012 Elsevier B.V. All rights reserved.

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