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 a great scientific depth and combines diverse research fields which makes it of interests for physicists as well as interdisciplinary researchers.
Cite
@article{arxiv.1202.1112,
title = {Recommender Systems},
author = {Linyuan Lü and Matus Medo and Chi Ho Yeung and Yi-Cheng Zhang and Zi-Ke Zhang and Tao Zhou},
journal= {arXiv preprint arXiv:1202.1112},
year = {2015}
}
Comments
97 pages, 20 figures (To appear in Physics Reports)