Neural Attentive Session-based Recommendation

  • Journal/Conference Proceedings
    Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM2017)
  • Publication Time
    2017
  • Authors
    Li, Jing, Pengjie Ren, Zhumin Chen, Zhaochun Ren, and Jun Ma.
We explore a hybrid encoder with an attention mechanism to model the user's sequential behavior and capture the user's main purpose in the current session, which are combined as a unified session representation later. We then compute the recommendation scores for each candidate item with a bi-linear matching scheme based on this unified session representation. We train NARM by jointly learning the item and session representations as well as their matchings.