| 基于文献指标与合著网络的《自动化学报》2011-2016年发表论文分析研究 |
| |
| 引用本文： | 赵学亮, 王涛, 王晓, 张楠, 孙星恺, 陆浩, 王坛. 基于文献指标与合著网络的《自动化学报》2011-2016年发表论文分析研究. 自动化学报, 2017, 43(12): 2232-2243. doi: 10.16383/j.aas.2017.y000007 |
| |
| 作者姓名： | 赵学亮 王涛 王晓 张楠 孙星恺 陆浩 王坛 |
| |
| 作者单位： | 1.中国科学院自动化研究所复杂系统管理与控制国家重点实验室 北京 100190;;2.中国科学院大学 北京 100049;;3.中国自动化学会 北京 100190;;4.国防科技大学系统工程学院 长沙 410073;;5.中国科学院自动化研究所 北京 100190;;6.北京理工大学计算机科学与技术学院 北京 100081 |
| |
| 基金项目： | 国家自然科学基金61533019国家自然科学基金71701206国家自然科学基金71232006 |
| |
| 摘 要： | 本文以《自动化学报》2011-2016年发表的文献数据为依据，以定量与定性相结合的方式探索研究自动化学科领域研究动态.首先，从发文量、影响因子、被引情况、下载量等指标角度对该刊过去6年的发展情况进行统计分析；随后，通过对关键词、论文作者与发文机构的数据挖掘，获取并呈现自动化学科热点研究领域、核心科研人员与机构；最后，构建作者合著网络，并对核心子网络的指标属性进行深入解析，刻画科研人员及机构间的合作关系.研究结果可为自动化领域科技工作者及关注自动化学科发展的人士了解学科动态，加强学术交流，以及促进群体合作提供一定的参考.
|
| 关 键 词： | 自动化学科 文献分析 合著网络 知识图谱 |
| 收稿时间： | 2017-08-15 |
A Literature Study on Acta Automatica Sinica During 2010 to 2016 with Bibliographic and Coauthorship Analysis |
| |
| ZHAO Xue-Liang, WANG Tao, WANG Xiao, ZHANG Nan, SUN Xing-Kai, LU Hao, WANG Tan. A Literature Study on Acta Automatica Sinica During 2010 to 2016 with Bibliographic and Coauthorship Analysis. ACTA AUTOMATICA SINICA, 2017, 43(12): 2232-2243. doi: 10.16383/j.aas.2017.y000007 |
| |
| Authors: | ZHAO Xue-Liang WANG Tao WANG Xiao ZHANG Nan SUN Xing-Kai LU Hao WANG Tan |
| |
| Affiliation: | 1. The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190;;2. University of Chinese Academy of Sciences, Beijing 100049;;3. Chinese Association of Automation, Beijing 100190;;4. The College of Information System and Management, National University of Defense Technology, Changsha 410073;;5. Institute of Automation, Chinese Academy of Sciences, Beijing 100190;;6. The School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081 |
| |
| Abstract: | A quantitative and qualitative study on research developments in automation field is conducted based on the papers published in Acta Automatica Sinica during 2011 to 2016 from the aspects of productivity, citations, topics, usage, and coauthorship networks. The most productive authors, institutions, and the most cited papers, most popular papers, as well as the most frequent topics and their trends are identified and analyzed. Social network methods are employed for revealing collaboration patterns among contributors through author-level coauthorship. It is indicated that the automation field has made tremendous progress and Acta Automatica Sinica has contributed significantly to accelerate the growth over that period. The findings can help scientists in automation field to understand research developments, enhance academic exchanges, and promote collaborations as well. |
| |
| Keywords: | Automation filed bibliographic analysis coauthorship network knowledge graph |
|
| 点击此处可从《自动化学报》浏览原始摘要信息 |
|
点击此处可从《自动化学报》下载全文 |
|
