Modeling Multi-interest News Sequence for News Recommendation

@article{Wang2022ModelingMN,
  title={Modeling Multi-interest News Sequence for News Recommendation},
  author={Rongyao Wang and Wenpeng Lu},
  journal={ArXiv},
  year={2022},
  volume={abs/2207.07331}
}
A session-based news recommender system recommends the next news to a user by modeling the potential interests embedded in a sequence of news read/clicked by her/him in a session. Generally, a user’s interests are diverse, namely there are multiple interests corresponding to different types of news, e.g., news of distinct topics, within a session. However, most of existing methods typically over-look such important characteristic and thus fail to distinguish and model the potential multiple… 

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