Knowledge Enhancement for Contrastive Multi-Behavior Recommendation

Author:

Xuan Hongrui1ORCID,Liu Yi1ORCID,Li Bohan2ORCID,Yin Hongzhi3ORCID

Affiliation:

1. Nanjing University of Aeronautics and Astronautics, Nanjing , China

2. Nanjing University of Aeronautics and Astronautics, Nanjing, China

3. The University of Queensland, Brisbane, Australia

Funder

National Natural Science Foundation of China

the?14th Five-Year Plan?Civil Aerospace Preresearch Project of China

Discovery Project

Postgraduate Research & Practice Innovation Program of NUAA

Australian Research Council Future Fellowship

Publisher

ACM

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Mixed-curvature knowledge-enhanced graph contrastive learning for recommendation;Expert Systems with Applications;2024-03

2. Explicit Behavior Interaction with Heterogeneous Graph for Multi-behavior Recommendation;Data Science and Engineering;2024-01-19

3. Multi-Behavior Job Recommendation with Dynamic Availability;Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region;2023-11-26

4. Self-Supervised Dynamic Hypergraph Recommendation based on Hyper-Relational Knowledge Graph;Proceedings of the 32nd ACM International Conference on Information and Knowledge Management;2023-10-21

5. Multi-Relational Contrastive Learning for Recommendation;Proceedings of the 17th ACM Conference on Recommender Systems;2023-09-14

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