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MHNF

The code impliments for paper "MHNF: Multi-hop Heterogeneous Neighborhood information Fusion graph representation learning” published in IEEE Transactions on Knowledge and Data Engineering(TKDE).

Note: Thanks to BUPT GAMMA Lab at Beijing University of Posts and Telecommunications. This work has been integrated into the OpenHGNN library, please click OpenHGNN(https://github.com/BUPT-GAMMA/OpenHGNN) to see the complete project.

Requirements and Installation

  • Python >= 3.6

  • PyTorch >= 1.7.1

  • DGL >= 0.7.0

  • CPU or NVIDIA GPU, Linux, Python3

If you find code useful, pllease consider cite our paper.

@article{sun2023mhnf, title={MHNF: Multi-Hop Heterogeneous Neighborhood Information Fusion Graph Representation Learning}, author={Sun, Yundong and Zhu, Dongjie and Du, Haiwen and Tian, Zhaoshuo}, journal={IEEE Transactions on Knowledge & Data Engineering}, volume={35}, number={07}, pages={7192--7205}, year={2023}, publisher={IEEE Computer Society} }