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A Collection Of Recent Ideas About Recommendation System
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recsys.md

Recent Ideas About Recommendation System

Recommendation Paradigm

  • Content-based -
  • Social/demographic - suggest items liked by friends, friends of friends, and demographic similar people
  • Contextual - recommend items based on current context
  • Collaborative Filtering - suggest items based on user behaviours

Articles

  1. Yanir Seroussi, The Wonderful World Of Recommendation Systems

Scientific Papers

  1. Joonseok Lee, Samy Bengio, Seungyeon Kim, Guy Lebanon and Yoram Singer, Local Collaborative Ranking, WWW 2014 (Best Student Paper Award)
  2. Hao Wang, Naiyan Wang and Dit-Yan Yeung, Collaborative Deep Learning for Recommender Systems, KDD 2015
  3. Hao Wang and Wu-Jun Li, Relational Collaborative Topic Regression for Recommender Systems, TKDE 2015
  4. Chong Wang and David M. Blei, Collaborative Topic Modeling for Recommending Scientific Articles, KDD 2011
  5. Ruslan Salakhutdinov and Andriy Mnih, Probabilistic Matrix Factorization, NIPS 2008
  6. Weston, Jason, Samy Bengio, and Nicolas Usunier. "Wsabie: Scaling up to large vocabulary image annotation." In IJCAI, vol. 11, pp. 2764-2770. 2011.
  7. Weston, Jason, Hector Yee, and Ron J. Weiss. "Learning to rank recommendations with the k-order statistic loss." In Proceedings of the 7th ACM conference on Recommender systems, pp. 245-248. ACM, 2013.
  8. Weston, Jason, Ron J. Weiss, and Hector Yee. "Nonlinear latent factorization by embedding multiple user interests." In Proceedings of the 7th ACM conference on Recommender systems, pp. 65-68. ACM, 2013.
  9. Yehuda Koren, Factorization meets the neighborhood: a multifaceted collaborative filtering model, KDD 2008.

Codes

  1. SVDFeature
  2. Recosystem in R and libmf
  3. Factorization Machine (libfm)
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