导师队伍

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黄文体简介

姓名:黄文体

职称/职务:校聘副教授

专 业:计算机科学与技术

研究方向:大数据与知识工程、知识图谱、自然语言处理

邮箱:wthuang@hnust.edu.cn

科研项目:

(1)教育厅优秀青年项目,“知识协同的神经网络关系抽取方法研究”,主持。

(2)科技部重点研发计划子课题,“特定***计算与解释机理”,主持。

(3)科技部科技创新2030--“新一代人工智能”重大项目,“医疗行为的时空协同表征理论与多维度主动感知方法”,参与。

(4)国家自然科学基金重点联合项目,“基于超算的跨网络大规模数据实时分析方法研究”,参与。

学术论文:

[1] Huang W, Mao Y, Long J, et al. Relation classification via knowledge graph enhanced transformer encoder[J]. Knowledge-Based Systems, 2020, 206: 106321.(中科院一区,JCR Q1, 影响因子:8.03)

[2] Huang W, Mao Y, Long J, et al. Quantum hacking of free-space continuous-variable quantum key distribution by using a machine-learning technique[J]. Physical Review A, 2019, 100(1): 012316.(中科院二区,NI检索,JCR Q2)

[3] Huang W, Mao Y, Long J, et al. Local­to­Global GCN with Knowledge­aware Representation for Distantly Supervised Relation Extraction[J]. Knowledge­BasedSystems, 2021.(中科院一区,JCR Q1,online,DOI10.1016/j.knosys.2021.107565,影响因子:8.03)

[4] Mao N, Zhong H, Huang W*. KGGCN: Knowledge-Guided Graph Convolutional Networks for Distantly Supervised Relation Extraction[J]. Applied Sciences, 2021,16(11):7734.(中科院三区,JCR Q2,)

[5] Long J, Wang Y, Huang W*, et al. Entity-Centric Fully Connected GCN for Relation Classification[J]. Applied Sciences, 2021, 4(11):1377. (中科院三区,JCR Q2)

[6] Mao Y, Wu X, Huang W*, et al. Monte Carlo-Based Performance Analysis for Underwater Continuous-Variable Quantum Key Distribution[J]. Applied Sciences, 2020, 10(17): 5744.(中科院三区,JCR Q2)

[7] Mao Y, Wang Y, Huang W*, et al. Continuous-variable quantum key distribution based on peak-compensation[J]. Acta PhysicaSinica, 2021, 70(11): 110302 (中科院三区,JCR Q4)

[8] Jun Long, Lei Liu, Hongxiao Fei, Yiping Xiang, Haoran Li, Wenti Huang*, and Liu Yang, Contextual Semantic-Guided Entity-Centric GCN forRelation Extraction[J], Mathematics, 2022, 10(8):1-17. (中科院二区,JCRQ1)

专利:

(1)龙军,黄文体一种基于知识图谱的学术圈构建方法专利号:201910668329.8

(2)龙军,黄文体一种基于增量学习的作者消歧方法专利号:201910691093.X