RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems

@article{Wang2018RippleNetPU,
  title={RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems},
  author={Hongwei Wang and Fuzheng Zhang and Jialin Wang and Miao Zhao and Wenjie Li and Xing Xie and Minyi Guo},
  journal={Proceedings of the 27th ACM International Conference on Information and Knowledge Management},
  year={2018}
}
  • Hongwei WangFuzheng Zhang M. Guo
  • Published 9 March 2018
  • Computer Science
  • Proceedings of the 27th ACM International Conference on Information and Knowledge Management
To address the sparsity and cold start problem of collaborative filtering, researchers usually make use of side information, such as social networks or item attributes, to improve recommendation performance. This paper considers the knowledge graph as the source of side information. To address the limitations of existing embedding-based and path-based methods for knowledge-graph-aware recommendation, we propose RippleNet, an end-to-end framework that naturally incorporates the knowledge graph… 

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