@article{Lü20121,
  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.},
  author = {Lü, Linyuan and Medo, Matúš and Yeung, Chi Ho and Zhang, Yi-Cheng and Zhang, Zi-Ke and Zhou, Tao},
  doi = {10.1016/j.physrep.2012.02.006},
  interhash = {408fbf13302368693d501271268cda03},
  intrahash = {9594d6b87d49d22b783b9c95da1f59af},
  issn = {0370-1573},
  journal = {Physics Reports},
  note = {Recommender Systems},
  number = 1,
  pages = {1 - 49},
  title = {Recommender systems},
  url = {http://www.sciencedirect.com/science/article/pii/S0370157312000828},
  volume = 519,
  year = 2012
}

@book{reference/rsh/2011,
  booktitle = {Recommender Systems Handbook},
  editor = {Ricci, Francesco and Rokach, Lior and Shapira, Bracha and Kantor, Paul B.},
  ee = {http://www.springerlink.com/content/978-0-387-85819-7},
  interhash = {fc9c45535069f00807f784abdd939d9f},
  intrahash = {49d1b9115124c64075d6c2c559504b22},
  isbn = {978-0-387-85819-7},
  publisher = {Springer},
  title = {Recommender Systems Handbook},
  url = {http://dblp.uni-trier.de/db/reference/rsh/rsh2011.html},
  year = 2011
}

@proceedings{Gunawardana2935,
  author = {Gunawardana, Asela and Shani, Guy},
  interhash = {441df9b673faf85aecc45babd8883069},
  intrahash = {49600df05a884106989d71dedcaa7e1b},
  page = {2935−2962},
  series = 2935,
  title = { A Survey of Accuracy Evaluation Metrics of Recommendation Tasks },
  url = {http://jmlr.csail.mit.edu/papers/v10/gunawardana09a.html},
  volume = {v10},
  year = 2009
}

@article{Burke02,
  author = {Burke, Robin},
  file = {Burke02.pdf:Burke02.pdf:PDF},
  interhash = {f40020400b8bc08adca29a987caf25d8},
  intrahash = {2dd27925f83ea7b04b5fc444938b866b},
  journal = {User Modeling and User Adapted Interaction},
  number = 4,
  owner = {stormerh},
  pages = {331-370},
  timestamp = {2006.11.20},
  title = {Hybrid Recommender Systems, Survey and Experiments},
  volume = 12,
  year = 2002
}

@article{citeulike:171426,
  author = {Adomavicius, G. and Tuzhilin, A.},
  citeulike-article-id = {171426},
  interhash = {42f7653127a823354d000ea95cf804be},
  intrahash = {55294392edb717922798725dd8be80b3},
  journal = {Knowledge and Data Engineering, IEEE Transactions on},
  keywords = {collaborative collaborative-filtering filtering mining personalization recommender recommender-systems systems},
  number = 6,
  pages = {734--749},
  priority = {2},
  title = {Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions},
  url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1423975},
  volume = 17,
  year = 2005
}