Collaborative Filtering: Weighted Nonnegative Matrix Factorization Incorporating User and Item Graphs

  title={Collaborative Filtering: Weighted Nonnegative Matrix Factorization Incorporating User and Item Graphs},
  author={Quanquan Gu and Jie Zhou and Chris H. Q. Ding},
Collaborative filtering is an important topic in data mining and has been widely used in recommendation system. In this paper, we proposed a unified model for collaborative filtering based on graph regularized weighted nonnegative matrix factorization. In our model, two graphs are constructed on users and items, which exploit the internal information (e.g. neighborhood information in the user-item rating matrix) and external information (e.g. content information such as user’s occupation and… CONTINUE READING
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Spectral Graph Theory (CBMS Regional Conference Series in Mathematics, No. 92) (Cbms Regional Conference Series in Mathematics)

  • Fan R.K. Chung
  • 1997
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