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Gang-Feng Ma
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2020 – today
- 2024
- [j10]Xuhua Yang, Dong Wei, Lian Zhang, Gang-Feng Ma, Xin-Li Xu, Haixia Long:
Task-related network based on meta-learning for few-shot knowledge graph completion. Appl. Intell. 54(8): 5961-5975 (2024) - [j9]Gang-Feng Ma, Xu-Hua Yang, Wei Ye, Xin-Li Xu, Lei Ye:
Network embedding based on high-degree penalty and adaptive negative sampling. Data Min. Knowl. Discov. 38(2): 597-622 (2024) - [j8]Gang-Feng Ma, Xuhua Yang, Haixia Long, Yanbo Zhou, Xin-Li Xu:
Robust social recommendation based on contrastive learning and dual-stage graph neural network. Neurocomputing 584: 127597 (2024) - [j7]Gang-Feng Ma, Xu-Hua Yang, Liang-Yu Gao, Ling-Hang Lian:
Adaptive denoising graph contrastive learning with memory graph attention for recommendation. Neurocomputing 610: 128595 (2024) - [j6]Gang-Feng Ma, Xu-Hua Yang, Yanbo Zhou, Haixia Long, Wei Huang, Weihua Gong, Sheng Liu:
Robust Preference-Guided Based Disentangled Graph Social Recommendation. IEEE Trans. Netw. Sci. Eng. 11(5): 4898-4910 (2024) - 2023
- [j5]Xuhua Yang, Gang-Feng Ma, Xin Jin, Haixia Long, Jie Xiao, Lei Ye:
Knowledge graph embedding and completion based on entity community and local importance. Appl. Intell. 53(19): 22132-22142 (2023) - [j4]Gang-Feng Ma, Xuhua Yang, Yanbo Zhou, Lei Ye:
Enhanced contrastive representation in network. Inf. Sci. 640: 119042 (2023) - [j3]Gang-Feng Ma, Xu-Hua Yang, Yue Tong, Yanbo Zhou:
Graph neural networks for preference social recommendation. PeerJ Comput. Sci. 9: e1393 (2023) - [j2]Xu-Hua Yang, Gang-Feng Ma, Fang-Nan Ma, Lei Ye, Yu-Di Zhang:
Attribute network joint embedding based on global attention. Pattern Recognit. Lett. 176: 189-195 (2023) - [j1]Xuhua Yang, Gang-Feng Ma, Xiangyu Zeng, Yuchao Pang, Yanbo Zhou, Yu-Di Zhang, Lei Ye:
Community Detection Based on Markov Similarity Enhancement. IEEE Trans. Circuits Syst. II Express Briefs 70(9): 3664-3668 (2023) - 2021
- [c1]Gang-Feng Ma, Xu-Hua Yang, Lei Ye, Yu-Jiao Huang, Peng Jiang:
Graph Convolutional Network Based on Higher-Order Neighborhood Aggregation. ICONIP (5) 2021: 334-342
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