Collaborative Filtering Using Dual Information Sources

  title={Collaborative Filtering Using Dual Information Sources},
  author={Jinhyung Cho and Kwiseok Kwon and Yongtae Park},
  journal={IEEE Intelligent Systems},
Conventional collaborative-filtering methods use only one information source to provide recommendations. Using two sources - similar users and expert users - enables more effective, more adaptive recommendations. Conventional CF methods suffer from a few fundamental limitations such as the cold-start problem, data sparsity problem, and recommender reliability problem. Thus, they have trouble dealing with high-involvement, knowledge-intensive domains such as e-learning video on demand. To… CONTINUE READING
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