[1]陆菁宇,张绍阳,黄文旎.学科发展状态的知识图谱构建[J].计算机技术与发展,2020,30(06):145-150.[doi:10. 3969 / j. issn. 1673-629X. 2020. 06. 028]
　LU Jing-yu,ZHANG Shao-yang,HUANG Wen-ni.Analysis of Development Status of Discipline Based on Knowledge Graph[J].COMPUTER TECHNOLOGY AND DEVELOPMENT,2020,30(06):145-150.[doi:10. 3969 / j. issn. 1673-629X. 2020. 06. 028]
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学科发展状态的知识图谱构建()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
30
期数:
2020年06期
页码:
145-150
栏目:
应用开发研究
出版日期:
2020-06-10

文章信息/Info

Title:
Analysis of Development Status of Discipline Based on Knowledge Graph
文章编号:
1673-629X(2020)06--0145-06
作者:
陆菁宇; 张绍阳; 黄文旎
长安大学 信息工程学院,陕西 西安 710064
Author(s):
LU Jing-yu; ZHANG Shao-yang; HUANG Wen-ni
School of Information Engineering,Chang’an University,Xi’an 710064,China
关键词:
交通信息工程及控制; 学科发展状态; 研究热点; 知识图谱; citespace
Keywords:
traffic information engineering and control; subject development status; research hotspot; knowledge graph; citespace
分类号:
TP301
DOI:
10. 3969 / j. issn. 1673-629X. 2020. 06. 028
摘要:
使用科学知识图谱的方法,对交通信息工程及控制学科发展状态进行探索。对学科发展状态进行分析可帮助各方深入认识学科的历史、现状和趋势。以2009-2018 年间交通信息工程及控制学科评估等级 B+以上的高校硕博士学位论文为分析对象,绘制科学知识图谱。分析知识图谱发现该学科科研技术种类多样, 并分别从公路交通、水路交通和铁路交通三个领域进行对比分析,发现该学科三个领域中的研究技术热点以及不同领域之间的科研技术共性。另外,通过构建交通信息工程及控制学科的技术演进知识图谱,呈现出该学科科研的技术发展脉络和知识流动趋势,并得出机器学习以及车联网技术为交通信息工程及控制学科未来科研的研究趋势。 为该学科的科研工作者提供深入研究的参考。
Abstract:
By using the scientific knowledge graph, the development status of traffic information engineering and control discipline is explored. The analysis of the development status of disciplines can help all parties to have a better under-standing of the history,current situation and trend of the discipline. The dissertations of master’s degree and doctor’s degree from universities with B+ or above in traffic information engineering and control disciplines from 2009 to 2018 to be chosen as object to draw the scientific knowledge graph.Discovering a wide variety of research techniques in the discipline, it also makes a comparative analysis of highway traffic, waterway traffic and railway traffic respectively, which shows the research focuses in three fields and technical commonalities among them. In addition,by analyzing the evolution of technology in the three fields,it presents the technological development thread and knowledge flow trend of scientific research in this discipline. And draw the research trend of machine learning and vehicle networking technology for future scientific research of traffic information engineering and control discipline, which provides a reference for further research for scientific researchers in this discipline.
更新日期/Last Update: 2020-06-10