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个人简介

牛广林,博士,北京航空航天大学人工智能研究院助理教授。2015年取得北京理工大学自动化专业学士学位,2022年取得北京航空航天大学计算机应用专业博士学位。主要研究方向包括规则和常识指导的知识图谱推理、时序知识图谱表示学习、多模态知识图谱构建与应用等,致力于探索数据和知识双轮驱动的人工智能方法,以第一作者在知识图谱领域顶级会议和期刊,包括AAAI、ACL、EMNLP、COLING、SIGIR和Neurocomputing发表多篇论文,其中,针对当前基于知识图谱嵌入的知识图谱推理方法缺乏可解释性的问题,提出了规则引导的神经-符号知识图谱推理方法、常识和数据联合驱动的两视角知识图谱推理技术,研究成果受到了国内外学术界和工业界的广泛关注。 曾参与国家重点研发计划、国家自然科学基金等项目,任AAAI、NeurlPS、EMNLP等顶会的程序委员会委员或审稿人,多次受邀在MLNLP、AI Time、人工智能前沿学生论坛分享技术报告,研究成果被专知、雷锋网、开放知识图谱等知名科技自媒体报道。曾被评为北航博士优秀毕业生,取得第一届“未来杯”知识图谱锦标赛一等奖,创建和维护知识图谱领域公众号“人工智能遇上知识图谱”。

近期论文

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Guanglin Niu, Bo Li, Yongfei Zhang, Shiliang Pu. CAKE: A Scalable Commonsense-Aware Framework For Multi-View Knowledge Graph Completion. ACL 2022 (CCF A, Top Conference). Long Paper. [Paper] [Code] Guanglin Niu, Bo Li, Yongfei Zhang, Yongpan Sheng, Chuan Shi, Jingyang Li, Shiliang Pu. Joint Semantics and Data-Driven Path Representation for Knowledge Graph Reasoning. Neurocomputing (Q1 SCI, IF: 5.719). [Paper] Guanglin Niu, Bo Li, Yongfei Zhang, Shiliang Pu. Perform like an Engine: A Closed-Loop Neural-Symbolic Learning Framework for Knowledge Graph Inference. COLING 2022 (CCF B, Top Conference). Long Paper. [Paper] [Code] Guanglin Niu, Yang Li, Chengguang Tang, Ruiying Geng, Jian Dai, Qiao Liu, Hao Wang, Jian Sun, Fei Huang, Luo Si. Relational Learning with Gated and Attentive Neighbor Aggregator for Few-Shot Knowledge Graph Completion. SIGIR 2021 (CCF A, Top Conference). Long paper. [Paper] [Code] Shan Yang, Yongfei Zhang, Guanglin Niu, Qinghua Zhao, Shiliang Pu. Entity Concept Enhanced Few-Shot Relation Extraction. ACL 2021 (CCF A, Top Conference). Short paper. [Paper] [Code] Guanglin Niu, Yang Li, et al. Path-Enhanced Multi-Relational Question Answering with Knowledge Graph Embeddings. Preprint Arxiv. [Paper] Guanglin Niu, Yongfei Zhang, Bo Li, Peng Cui, Si Liu, Jingyang Li and Xiaowei Zhang. Rule-Guided Compositional Representation Learning on Knowledge Graphs. AAAI 2020 (CCF A, Top Conference). Long paper (Spotlight). [Paper] [Code] Guanglin Niu, Bo Li, Yongfei Zhang, Shiliang Pu and Jingyang Li. AutoETER: Automated Entity Type Representation with Relation-Aware Attention for Knowledge Graph Embedding. EMNLP 2020 Findings (CCF B, Top Conference). Long paper. [Paper] [Code] Ming Xin, Jin Zheng, Bo Li, Guanglin Niu and Miaohui Zhang. Real-time object tracking via self-adaptive appearance modeling. Neurocomputing. Q1, IF: 5.719. [Paper] SURVEY 李晶阳, 牛广林, 唐呈光, 余海洋, 李杨, 付彬, 孙健. 万字综述:行业知识图谱构建最新进展. PaperWeekly. [Paper] 李杨, 李晶阳, 牛广林, 唐呈光, 付彬, 余海洋, 孙健. 知识表示与融入技术前沿进展及应用. PaperWeekly. [Paper]

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