Analytics of Lastest Research Progress in Automation Discipline Based on Academic Knowledge Mapping
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摘要: 现今,以自动控制和信息处理为核心的自动化技术已经成为推动生产力发展、改善人类生活以及促进社会前进的源动力之一.全面了解自动化学科的最新发展态势,对本领域科研部门、科研人员进行工作的规划与实施有着重要的参考价值,本文以2011年~2013年期间88种期刊的46242篇文章作为数据基础,采用文献计量学、社会网络分析等方法进行数据解析,通过知识图谱定量描绘出本领域5个方向(控制理论与控制工程、模式识别与智能系统、系统工程、检测技术与自动化装置、导航、制导与控制)的最新研究态势.结果表明,本领域国内研究热点与国际研究热点各有侧重,国内机构在国际研究中的地位逐步提高,特别地,华人群体在本领域的研究中起到重要的推动作用.Abstract: Nowadays, automation science and technology based on automatic control and information processing has become an essential impetus to productive forces and human life. So a comprehensive understanding of the latest research progress in this discipline is essential for its significant reference value to scholars and research institutions. In this paper, the automation science and technology discipline is divided into five research fields, which are specifically defined as control theory and engineering, pattern recognition and intelligent systems, measurement technology and automatic equipment, navigation and guidance, and systems engineering. Each field is depicted by analyzing and mapping the data from 46242 academic articles published on 88 journals during 2011~2013. The results show that the research interests are different between domestic and abroad, and that the domestic institutions and ethnic Chinese scholars have played an important role in promoting the development of automation science and technology.
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Key words:
- Data analytics /
- knowledge mapping /
- automation discipline /
- research progress
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[1] Wang Fei-Yue. The destiny: towards knowledge automation-preface of the special issue for the 50th anniversary of Acta Automatica Sinica. Acta Automatica Sinica, 2013, 39(11): 1741-1743 (王飞跃. 天命唯新: 迈向知识自动化——《自动化学报》创刊50周年专刊序. 自动化学报, 2013, 39(11): 1741-1743) [2] Wang Fei-Yue. Evolution of knowledge generation and scientific decision-making: big data and opensource intelligence analytics for research intelligent. Bullitin of Chinese Academy of Science, 2012, 27(5): 527-537 (王飞跃. 知识产生方式和科技决策支撑的重大变革——面向大数据和开源信息的科技态势解析与决策服务. 中国科学院院刊, 2012, 27(5): 527-537) [3] Lai G P, Zhang Q P, Wen D, Gao Y Q. A prototype of the next-generation journal system for ITS: academic social networking and media based on Web 3. 0. IEEE Transactions on Intelligent Transportation Systems, 2012, 13(2): 1078-1087 [4] Wang F Y. Publication and impact: a bibliographic analysis. IEEE Transactions on Intelligent Transportation Systems, 2010, 11(2): 250 [5] Zhang Q P, Feng Z, Li X, Zheng X L, Zhang L. 25 years collaborations at IEEE intelligent systems. IEEE Intelligent Systems, 2010, 25(6): 67-75 [6] Li L J, Li X, Cheng C J, Chen C, Ke G Y, Zeng D D, Scherer W T. Research collaboration and ITS topic evolution: 10 years at T-ITS. IEEE Transactions on Intelligent Transportation Systems, 2010, 11(3): 517-523 [7] Ye Pei-Jun, Lü Yi-Sheng, Ji Jing-Chu. Literature analysis for traffic simulation and computational experiments based on social networks. Acta Automatica Sinica, 2013, 39(9): 1402-1412(叶佩军, 吕宜生, 吉竟初. 基于社会网络视角的交通仿真和计算实验研究分析. 自动化学报, 2013, 39(9): 1402-1412) [8] Wang Fei-Yue. Scientific collaboration trends in 21 century, Science of Team Science (SciTS). Science and Technology Review, 2011, 29(12): 81(王飞跃. SciTS: 21世纪科技合作的灯塔. 科技导报, 2011, 29(12): 81) [9] Wang F Y. From AI to SciTS: team science and research intelligence. IEEE Intelligent Systems, 2011, 26(3): 2-4 [10] Zheng X L, Ke G Y, Zeng D, Ram S. Next-generation team-science platform for scientific collaboration. IEEE Intelligent Systems, 2011, 26(6): 72-76 [11] Zhang Q, Wang F Y, Zeng D, Wang T. Understanding crowd-powered search groups: a social network perspective. PLoS ONE, 2012, 7(6): e39749 [12] Wang F Y, Lai G, Tang S M. An application specific knowledge engine for researches in intelligent transportation systems. In: Proceedings of the 7th International Conference on Intelligent Transportation Systems. Washington D.C., USA: IEEE, 2004. 841-846 [13] Oyama S, Kokubo T, Ishida T. Domain-specific web search with keyword spices. IEEE Transactions on Knowledge and Data Engineering, 2004, 16(1): 17-27 [14] Walczak S. Knowledge-based search in competitive domains. IEEE Transactions on Knowledge and Data Engineering, 2003, 15(3): 734-743 [15] QIU Tao-Rong, LIU Qing, HUANG Hou-Kuan. A granular computing approach to knowledge discovery in relational databases. Acta Automatica Sinica, 2009, 35(8): 1071-1079(邱桃荣, 刘清, 黄厚宽. 关系数据库中知识发现的一种粒计算方法. 自动化学报, 2009, 35(8): 1071-1079) [16] Albert R, Barabasi A L. Statistical mechanics of complex networks. Reviews of Modern Physics, 2002, 74(1): 47-97 [17] Boccaletti S, Latora V, Moreno Y, Chavez M, Hwang D. Complex networks: structure and dynamics. Physics Reports, 2006, 424(4-5): 175-308 [18] Newman M E J. Scientific collaboration networks II. Shortest paths, weighted networks, and centrality. Physical Review E, 2001, 64(1): 16-132 [19] Newman M E J. Co-authorship networks and patterns of scientific collaboration. Proceedings of the National Academy of Sciences of the United States of America, 2004, 101(1): 5200-5205 [20] Newman M E J. Detecting community structure in networks. The European Physical Journal B——Condensed Matter and Complex Systems, 2004, 38(2): 321-330 [21] Varun G, Albert H S, Steven J S. An assessment of individual and institutional research productivity in MIS. ACM SIGMIS Database, 1992, 23(4): 5-9 [22] Susan A, John P. An evaluation of research productivity in academic IT. Journal Communications of the AIS, 2000, 3(2): 3 [23] Huang H H, Hsu J S C. An evaluation of publication productivity in information systems: 1999 to 2003. Communications of the Association for Information Systems, 2005, 15(1): 555-564 [24] Van Eck N J, Waltman L. Text mining and visualization using VOSviewer. ISSI Newsletter, 2011, 7(3): 50-54 [25] Van Eck N J, Waltman L. How to normalize co-occurrence data an analysis of some well-known similarity measures. Journal of the American Society for Information Science and Technology, 2009, 60(8): 1635-1651 [26] de Nooy W, MrvarA, Batagelj V. Exploratory Social Network Analysis with Pajek. Cambridge: Cambridge University Press, 2005. 303-306 [27] Batagelj V, Mrvar A. Pajek-program for large network analysis. Connections, 1998, 21(2): 47-57
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