The architecture of this model combines each user's features and his historical event lists by sequence-to-sequence (Seq2Seq) structure and make predictions based on his recent event lists. We also ...

To fill this gap, we propose two attention-mechanism-based encoder–decoder models that incorporate multisource ... with a success rate of nearly 50%. Our model achieved competitive results, mainly ...