RECOMMENDATION BASED ON GRAPH NEURAL NETWORK WITH ENTITY SIMILARITY AND RELATION FUSION

Xie Jin,∗,∗∗ Xianfeng Weng,∗∗∗ Xinru Fan,∗∗∗∗ Mohamad Fadli Zolkipli,∗∗ Yufeng Chen,∗ Zhengtao Xiang,∗ and Minghao Yue∗

References

  1. [1] F. Wen, H. Wang, G. Gui, H. Sari, and F. Adachi, Polarizedintelligent reflecting surface aided 2D-DOA estimation for NLoSsources, IEEE Transactions on Wireless Communications,23(7), 2024, 8085–8098, DOI:10.1109/TWC.2023.3348520.
  2. [2] H. Zhou, Z. Wang, G. Min, and H. Zhang, UAV-Aidedcomputation offloading in mobile-edge computing networks: Astackelberg game approach, IEEE Internet of Things Journal,10(8), 2023, 6622–6633.
  3. [3] F. Wen, G. Gui, H. Gacanin, and H. Sari, Compressivesampling framework for 2D-DOA and polarization estimationin mmWave polarized massive MIMO systems, IEEE Trans-actions on Wireless Communications, 22(5), 2023, 3071–3083.
  4. [4] F. Wen, D. Ren, and X. Zhang, Fast localizing for anonymousUAVs oriented toward polarized massive MIMO systems, IEEEInternet of Things Journal, 10(22), 2023, 20094–20106.
  5. [5] F. Wen, J. Shi, G. Gui, H. Gacanin, and O.A. Dobre, 3DPositioning method for anonymous UAV based on bistaticpolarized MIMO radar, IEEE Internet of Things Journal,2023, 10(1), 815–827.
  6. [6] L. Cai, T. Lai, L. Wang, Y. Zhou, and Y. Xiong, Graphconvolutional network combining node similarity associationand layer attention for personalized recommendation, Eng.Appl. Artif. Intell., 121, 2023, 105981.
  7. [7] Z. Wang, W. Wei, G .Cong, X.L. Li, X.L. Mao, and M Qiu,Global context enhanced graph neural networks for session-based recommendation,Proceedings of the 43rd InternationalACM SIGIR Conference on Research and Development inInformation Retrieval, New York, NY, USA, 2020, 169–178.
  8. [8] Q. Guo, Y. Shao, C. Yan, and Y Shi, Collaborative filteringhybrid recommendation algorithm incorporating knowledgegraph, /Proceedings of the 2023 4th International Conferenceon Computing, Networks and Internet of Things, New York,NY, USA, 2023, 494–499.
  9. [9] F. Wen, Z. Zhang, H. Sun, G. Gui, H. Sari, and F. Adachi,2D-DOA estimation auxiliary localization of anonymous UAVusing EMVS-MIMO radar, IEEE Internet of Things Journal,11(9), 2024, 16255–16266, DOI: 10.1109/JIOT.2024.3351136.
  10. [10] H. Wang, M. Zhao, X. Xie, W. Li, and M. Guo, Knowledge graphconvolutional networks for recommender systems, ProceedingThe World Wide Web Conference, New York, NY, USA, 2019,3307–3313.
  11. [11] W.X. Zhao, S. Mu, Y. Hou, Z. Lin, Y. Chen, X. Pan, K.Li, Y. Lu, H. Wang, C. Tian, Y. Min, Z. Feng, X. Chen,P. Wang, W. Ji, Y. Li, X. Wang, J.-R. Wen, Recbole:Towards a unified, comprehensive and efficient frameworkfor recommendation algorithms, Proceedings of the 30thACM International Conference On Information & KnowledgeManagement, New York, NY, USA, 2021, 4653–4664.
  12. [12] J. Wu, F. Wen, and J. Shi, Direction finding in bistaticMIMO radar with direction-dependent mutual coupling, IEEECommunications Letters, 25(7), 2021, 2231–2234.
  13. [13] J. Wu, F. Wen, and J. Shi, Fast angle estimation inMIMO system with direction-dependent mutual coupling, IEEECommunications Letters, 25(9), 2021, 2913–2917.
  14. [14] X. He, K. Deng, X. Wang, Y. Li, Y. Zhang, and M. Wang,Lightgcn: Simplifying and powering graph convolution networkfor recommendation, Proceedings of the 43rd InternationalACM SIGIR Conference on Research and Development inInformation Retrieval, New York, NY, USA, 2020, 639–648.
  15. [15] H. Wang, F. Zhang, J. Wang, M. Zhao, W. Li, X. Xie,and M. Guo, Ripplenet: Propagating user preferences on theknowledge graph for recommender systems, Proceedings ofthe 27th ACM International Conference on Information andKnowledge Management, New York, NY, USA, 2018, 417–426.
  16. [16] X. Wang, X. He, Y. Cao, M. Liu, and T.S. Chua, KGAT:Knowledge graph attention network for recommendation, Pro-ceedings of the 25th ACM SIGKDD International Conferenceon Knowledge Discovery & Data Mining, New York, NY, USA,2019, 950–958.
  17. [17] H. Sun, B. Li, Z. Dan, W. Hu, B. Du, W. Yang, and J.Wan, Multi-level feature interaction and efficient non-localinformation enhanced channel attention for image dehazing,Neural Networks, 163, 2023, 10–27.
  18. [18] H. Sun, Z. Luo, D. Ren, W. Hu, B. Du, W. Yang, J. Wan, andL. Zhang, Partial siamese with multiscale bi-codec networksfor remote sensing image haze removal, IEEE Transactions onGeoscience and Remote Sensing, 61, 2023, 4106516.
  19. [19] J. Shen, S. Lyu, X. Zhang, and Y. Lu, Change, Detectionvia graph matching and multi-view geometric constraints,Proceeding IEEE International Conference on Image Processing(ICIP), 2019, 4035–4039.
  20. [20] Y. Chen, H. Cao, Z. Xiang, B. Chen, Y. Ma, and Y. Zhang,Vehicle lane-change intention recognition based on BiLSTMAttention model for the Internet of vehicles, Proceedings ofthe Institution of Mechanical Engineers, Part-D: Journal ofAutomobile Engineering, 2024, submitted for publication, doi:10.1177/09544070241240225.
  21. [21] B. Li, H. Zhang, and X. Shi , A novel path planning forAUV based on dung beetle optimisation algorithm with deepQ-network, International Journal of Robotics and Automation,40, 2025, 65–73.
  22. [22] K. Tuerxun, Intelligent synthesis Technology of Chinese speechfor speech Navigation, International Journal of Robotics andAutomation, 39, 2024, 504–514.
  23. [23] S. Wu, Y. Tang, Y. Zhu, L. Wang, X. Xie, and T. Tan,Session-based recommendation with graph neural networks,2018, arXiv:1811.00855.

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