陈虹枢 - 北京理工大学 - 管理与经济学院

个人简介

陈虹枢，北京理工大学管理与经济学院管理科学与物流系助理教授、特别副研究员，博士生导师。2015年于北京理工大学获得管理学博士学位，2016年于悉尼科技大学获得软件工程博士学位，曾任悉尼科技大学工程与信息学院科研助理及助教。主要研究方向为知识管理与创新管理、科技文本挖掘与知识发现，重点关注信息多源、主体异质的科学研究活动在关系挖掘、机制分析及机会发现过程中遇到的新问题和新挑战。围绕融合机器学习的科学计量、基于复杂网络的科研数据建模及分析、以及大规模科技文本处理等研究主题，已在IEEE Transactions on Engineering Management, IEEE Transactions on Cybernetics, Technological Forecasting and Social Change, Scientometrics等国际期刊，以及波特兰工程与技术管理国际会议（PICMET）等领域内知名国际会议中发表学术论文30余篇（ESI高被引1篇），担任包括Research Policy, IEEE Transactions on Engineering Management, Technological Forecasting and Social Change, Scientometrics, Technology in Society, Knowledge-Based Systems在内的多个SCI/SSCI国际期刊的论文评阅人，主持及参与多项国家自然科学基金项目。获奖情况 2022年，北京理工大学优秀硕士学位论文指导教师 2022年，第十二届全国大学生电子商务“创新、创意及创业”挑战赛北京赛区省级选拔赛二等奖（指导教师）

研究领域

主要研究方向为知识管理与创新管理、科技文本挖掘与知识发现，重点关注信息多源、主体异质的科学研究活动在关系挖掘、机制分析及机会发现过程中遇到的新问题和新挑战。

近期论文

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CHEN, H., SONG, X., JIN, Q. & WANG, X. 2022. Network Dynamics in University-industry Collaboration: A Collaboration-knowledge Dual-layer Network Perspective. Scientometrics, 127(11), 6637-6660. (SCI/SSCI, FMS B, 3.801) CHEN, H., JIN, Q., WANG, X. & XIONG, F. 2022. Profiling academic-industrial collaborations in bibliometric-enhanced topic networks: A case study on digitalization research. Technological Forecasting and Social Change, 175, 121402. (SSCI, FMS B, 10.884) JIN, Q., CHEN, H.*, WANG, X., MA, T. & XIONG, F. 2022. Exploring funding patterns with word embedding-enhanced organization–topic networks: a case study on big data. Scientometrics, 127(9), 5415-5440. (一作为所指导研究生，SCI/SSCI, FMS B, 3.801) CHEN, H., WANG, X., PAN, S. & XIONG, F. 2021. Identify Topic Relations in Scientific Literature Using Topic Modeling. IEEE Transactions on Engineering Management, 68, 1232-1244. (SCI, FMS A, 8.702) XIONG, F., SHEN, W., CHEN, H.*, PAN, S., WANG, X. & YAN, Z. 2020. Exploiting Implicit Influence from Information Propagation for Social Recommendation. IEEE Transactions on Cybernetics, 50, 4186-4199. (SCI, FMS B,19.118) Zhang, Y.，Lu, J., Liu, F., Liu, Q., Porter, A., Chen, H.*, Zhang, G. 2018. Does deep learning help topic extraction? A kernel k-means clustering method with word embedding, Journal of Informetrics, 12(4), 1099-1117. (SCI, FMS B, 4.373) Chen, H., Zhang, G., Zhu, D., Lu, J. 2017. Topic-based technological forecasting based on patent data: A case study of Australian patents from 2000 to 2014. Technological Forecasting and Social Change, 119, 39-52. (SSCI, FMS B, 10.884) Zhang, Y., Chen, H.*, Lu, J., Zhang, G. 2017. Detecting and predicting the topic change of Knowledge-based Systems: A topic-based bibliometric analysis from 1991 to 2016. Knowledge-Based Systems, 133, 255-268. (SCI, JCR Q1, 8.139) CHEN, H., ZHANG, Y., JIN, Q. & WANG, X. 2022. Exploring Patterns of Academic-Industrial Collaboration for Digital Transformation Research: A Bibliometric-Enhanced Topic Modeling Method. 2022 Portland International Conference on Management of Engineering and Technology (PICMET), 2022 August 7 - August 11, Portland, OR, United states. (EI) CHEN, H., SONG, X. 2021, Collaboration and knowledge networks: A framework on analyzing evolution of university-industry collaborative innovation. Proceedings of the 1st Workshop on AI + Informetrics，AII2021；2871，33-46 (EI) Chen, H., Song, Y., Wang, X., Wang, X., Wang, X., Yu, M. 2019. Research Topic Recommendation based on Latent Dirichlet Allocation. 2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 14-16 Nov. 2019, 637-643 (EI) 陈虹枢, 宋亚慧, 金茜茜, 汪雪锋. 动态主题网络视角下的突破性创新主题识别:以区块链领域为例, 图书情报工作, 2022, 66(10): 45-58. (CSSCI)