Special Issue on Machine Learning in Scientometrics
1★, 2★ Corresponding author
- 1PES University and Center for AstroInformatics, Bangalore, Karnataka, INDIA.
- 2Centre for Studies in Social Sciences, Calcutta and University of Bonn, GERMANY.
CORRESPONDENCE
Snehanshu Saha
PES University and Center for AstroInformatics, Bangalore, Karnataka, INDIA.
Volume 8, Issue 2s · pp. s1 · 2019 · DOI: 10.5530/jscires.8.2.20
ABSTRACT
Scientometrics is a domain that performs a quantitative and qualitative assessment of research and scientific progress. The field has earned popularity in last few years owing to the need to measure research outputs at individual, institutional and geographical levels. As a result of this need, different parameters are brought-up and various databases like Scopus, Web of Science and Google scholar are built for computation of these parameters. The data generated and stored as a result of proliferation of research papers and other scientific activities is vast. Analysis of the data cannot be performed without the intervention of sophisticated tools and techniques. Consequently, the use of Machine leaning algorithms for carrying out tasks like classification, regression, clustering and associations on these databases becomes imminent.
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Saha, S., & Kar, S. (2019). Special Issue on Machine Learning in Scientometrics. Journal of Scientometric Research, 8(2s), s1. https://doi.org/10.5530/jscires.8.2.20
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© 2019 Author(s)
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