Corpus ID: 210164537

Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation

@article{Dong2019AsymmetricalHN,
  title={Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation},
  author={Xin Dong and Jingchao Ni and Wei Cheng and Zhengzhang Chen and Bo Zong and Dongjin Song and Yanchi Liu and Haifeng Chen and Gerard de Melo},
  journal={ArXiv},
  year={2019},
  volume={abs/2001.04346}
}
  • Xin Dong, Jingchao Ni, +6 authors Gerard de Melo
  • Published in AAAI 2019
  • Computer Science
  • Recently, recommender systems have been able to emit substantially improved recommendations by leveraging user-provided reviews. Existing methods typically merge all reviews of a given user or item into a long document, and then process user and item documents in the same manner. In practice, however, these two sets of reviews are notably different: users' reviews reflect a variety of items that they have bought and are hence very heterogeneous in their topics, while an item's reviews pertain… CONTINUE READING

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