Research Trend on Data Mining: A Scientometric Study during 2011-2020, based on Web of Science
Author(s): Dr. S. Baskaran
Abstract – The present study analyzing the publication trends on data mining research output based on Web of Science database. During 2011-2020, the database contained 46446 publications were published in the field. The average number of publications per year was 46446 and the highest number of publications 7680 was published in 2020. Relative Growth Rate is decreasing throughout the study period and corresponding Doubling time is increasing. Authors from China have contributed maximum number of publications compared to the other countries and India stood 7th rank in terms of productivity in this period. The most prolific author is Zhang, Y who contributed 245 (0.53%) publications followed by Liu, Y with 222 (0.48%) publications, Li, J with 214 (0.46%) publications. Chinese Academy of Science, China is the most productive institution with 1248 (2.69%) publications followed by University of California System, USA with 833 (1.79%) publications, China University Mining Technology, China with 797 (1.72%) publications. The most productive source title is IEEE Access the list with the highest number of publications 1188 (25.57%), followed by Expert systems with applications with a share of 794 (1.71%) publications. PLOS one occupy the third position with 656 (1.41%) publications.
Chinese Academy of Science, China with 1248 (2.69%) publications is the most productive institutions in the field of data mining research followed by.
Keywords - Data mining, Scientometric analysis, Annual growth rate, Relative growth rate and Doubling time.
DOI URL: https://doi.org/10.26761/ijrls.7.4.2021.1457
Cite This Article As: Baskaran, S. (2021). Research Trend on Data Mining: A Scientometric Study during 2011-2020, based on Web of Science. International Journal of Research in Library Science (IJRLS), 7(4) 76-84. www.ijrls.in
Copyright © 2021 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0.
Paper ID: IJRLS-1457 Page: 76-84 Publication Date: 27 October 2021