A Group-Specific Recommender System

@article{Bi2017AGR,
  title={A Group-Specific Recommender System},
  author={Xuan Bi and A. Qu and Junhui Wang and Xiaotong Shen},
  journal={Journal of the American Statistical Association},
  year={2017},
  volume={112},
  pages={1344 - 1353}
}
ABSTRACT In recent years, there has been a growing demand to develop efficient recommender systems which track users’ preferences and recommend potential items of interest to users. In this article, we propose a group-specific method to use dependency information from users and items which share similar characteristics under the singular value decomposition framework. The new approach is effective for the “cold-start” problem, where, in the testing set, majority responses are obtained from new… Expand
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