Compressed knowledge transfer via factorization machine for heterogeneous collaborative recommendation

@article{Pan2015CompressedKT,
  title={Compressed knowledge transfer via factorization machine for heterogeneous collaborative recommendation},
  author={Weike Pan and Zhuode Liu and Zhong Ming and Hao Zhong and Xin Wang and Congfu Xu},
  journal={Knowl.-Based Syst.},
  year={2015},
  volume={85},
  pages={234-244}
}
Collaborative recommendation has attracted various research works in recent years. However, an important problem setting, i.e., ‘‘a user examined several items but only rated a few’’, has not received much attention yet. We coin this problem heterogeneous collaborative recommendation (HCR) from the perspective of users’ heterogeneous feedbacks of implicit examinations and explicit ratings. In order to fully exploit such different types of feedbacks, we propose a novel and generic solution… CONTINUE READING
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