ATBRG: Adaptive Target-Behavior Relational Graph Network for Effective Recommendation

@article{Feng2020ATBRGAT,
  title={ATBRG: Adaptive Target-Behavior Relational Graph Network for Effective Recommendation},
  author={Yufei Feng and Binbin Hu and Fuyu Lv and Qingwen Liu and Zhiqiang Zhang and Wenwu Ou},
  journal={Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval},
  year={2020}
}
  • Yufei FengBinbin Hu Wenwu Ou
  • Published 25 May 2020
  • Computer Science
  • Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval
Recommender system (RS) devotes to predicting user preference to a given item and has been widely deployed in most web-scale applications. Recently, knowledge graph (KG) attracts much attention in RS due to its abundant connective information. Existing methods either explore independent meta-paths for user-item pairs over KG, or employ graph neural network (GNN) on whole KG to produce representations for users and items separately. Despite effectiveness, the former type of methods fails to… 
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17 Citations
Highly Influential Citations
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Background Citations
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Methods Citations
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