文章基本信息

标题：Quantum Machine Learning: A Scientometric Assessment of Global Publications during 1999-2020
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作者：S. M. Dhawan ; B. M. Gupta ; Ghouse Modin N. Mamdapur 等
期刊名称：International Journal of Knowledge Content Development & Technology
印刷版ISSN：2234-0068
电子版ISSN：2287-187X
出版年度：2021
卷号：11
期号：3
页码：29-44
DOI：10.5865/IJKCT.2021.11.3.029
语种：English
出版社：Research Institute for Knowledge Content Development & Technology
摘要：The study provides a quantitative and qualitative description of global research in the domain of quantum machine learning (QML) as a way to understand the status of global research in the subject at the global, national, institutional, and individual author level. The data for the study was sourced from the Scopus database for the period 1999-2020. The study analyzed global research output (1374 publications) and global citations (22434 citations) to measure research productivity and performance on metrics. In addition, the study carried out bibliometric mapping of the literature to visually represent network relationship between key countries, institutions, authors, and significant keyword in QML research. The study finds that the USA and China lead the world ranking in QML research, accounting for 32.46% and 22.56% share respectively in the global output. The top 25 global organizations and authors lead with 35.52% and 16.59% global share respectively. The study also tracks key research areas, key global players, most significant keywords, and most productive source journals. The study observes that QML research is gradually emerging as an interdisciplinary area of research in computer science, but the body of its literature that has appeared so far is very small and insignificant even though 22 years have passed since the appearance of its first publication. Certainly, QML as a research subject at present is at a nascent stage of its development.