A^3NCF: An Adaptive Aspect Attention Model for Rating Prediction

@inproceedings{Cheng2018A3NCFAA,
  title={A^3NCF: An Adaptive Aspect Attention Model for Rating Prediction},
  author={Zhiyong Cheng and Ying Ding and Xiangnan He and Lei Zhu and Xuemeng Song and M. Kankanhalli},
  booktitle={IJCAI},
  year={2018}
}
Current recommender systems consider the various aspects of items for making accurate recommendations. [] Key Method Specifically, we design a new topic model to extract user preferences and item characteristics from review texts. They are then used to 1) guide the representation learning of users and items, and 2) capture a user’s special attention on each aspect of the targeted item with an attention network. Through extensive experiments on several largescale datasets, we demonstrate that our model…

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