MRLR: Multi-level Representation Learning for Personalized Ranking in Recommendation

  title={MRLR: Multi-level Representation Learning for Personalized Ranking in Recommendation},
  author={Zhu Sun and Jie Yang and Jie Zhang and Alessandro Bozzon and Yu Chen and Chi Xu},
Representation learning (RL) has recently proven to be effective in capturing local item relationships by modeling item co-occurrence in individual user’s interaction record. However, the value of RL for recommendation has not reached the full potential due to two major drawbacks: 1) recommendation is modeled as a rating prediction problem but should essentially be a personalized ranking one; 2) multi-level organizations of items are neglected for fine-grained item relationships. We design a… CONTINUE READING


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