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International Journal of Machine Learning and Cybernetics
Published in: International Journal of Machine Learning and Cybernetics 3/2020

04-11-2019 | Original Article

Bibliometric analysis of support vector machines research trend: a case study in China

Authors: Dejian Yu, Zeshui Xu, Xizhao Wang

Published in: International Journal of Machine Learning and Cybernetics | Issue 3/2020

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Abstract

Support vector machine (SVM) is a widely used algorithm in the field of machine learning, and it is a research hotspot in the field of data mining. In order to fully understand the historical progress and current situation of SVM researches, as well as its future development trend in China, this paper conducts a comprehensive bibliometric study based on the publications from web of science database by Chinese scholars in this field. First, this paper focuses on some of the basic characteristics of the research publications of SVM in China, including important journals, research institutions and countries/regions, most cited publications, and so on. Then, based on the knowledge mapping software VOSviewer, the cooperation between other countries and China as well as the cooperation between research institutions in China are explored. Finally, VOSviewer based bibliometric visualization graphics are used to identify the changes of the research hotspots in the SVM field. This paper provides a relatively broad perspective for the evaluation of SVM scientific researches, and reveals the development trend in this field.
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Appendix
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Metadata
Title
Bibliometric analysis of support vector machines research trend: a case study in China
Authors
Dejian Yu
Zeshui Xu
Xizhao Wang
Publication date
04-11-2019
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 3/2020
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-019-01028-y

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