Incorporating Context Correlation into Context-aware Matrix Factorization

  title={Incorporating Context Correlation into Context-aware Matrix Factorization},
  author={Yong Zheng and Bamshad Mobasher and Robin D. Burke},
Context-aware recommender systems (CARS) go beyond traditional recommender systems, that only consider users’ profiles, by adapting their recommendations also to users’ contextual situations. Several contextual recommendation algorithms have been developed by incorporating context into recommendation algorithms in different ways. The most effective approaches try to model deviations in ratings among contexts, but ignore the correlations that may exist among these contexts. In this paper, we… CONTINUE READING

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