Ezugwu Absalom E, Oyelade Olaide N, Ikotun Abiodun M, Agushaka Jeffery O, Ho Yuh-Shan
Unit for Data Science and Computing, North-West University, 11 Hoffman Street, Potchefstroom, 2520 South Africa.
Department of Computer Science, Faculty of Physical Sciences, Ahmadu Bello University, Zaria, Nigeria.
Arch Comput Methods Eng. 2023 Apr 29:1-31. doi: 10.1007/s11831-023-09930-z.
The machine learning (ML) paradigm has gained much popularity today. Its algorithmic models are employed in every field, such as natural language processing, pattern recognition, object detection, image recognition, earth observation and many other research areas. In fact, machine learning technologies and their inevitable impact suffice in many technological transformation agendas currently being propagated by many nations, for which the already yielded benefits are outstanding. From a regional perspective, several studies have shown that machine learning technology can help address some of Africa's most pervasive problems, such as poverty alleviation, improving education, delivering quality healthcare services, and addressing sustainability challenges like food security and climate change. In this state-of-the-art paper, a critical bibliometric analysis study is conducted, coupled with an extensive literature survey on recent developments and associated applications in machine learning research with a perspective on Africa. The presented bibliometric analysis study consists of 2761 machine learning-related documents, of which 89% were articles with at least 482 citations published in 903 journals during the past three decades. Furthermore, the collated documents were retrieved from the Science Citation Index EXPANDED, comprising research publications from 54 African countries between 1993 and 2021. The bibliometric study shows the visualization of the current landscape and future trends in machine learning research and its application to facilitate future collaborative research and knowledge exchange among authors from different research institutions scattered across the African continent.
机器学习（ML）范式如今已广受欢迎。其算法模型被应用于各个领域，如自然语言处理、模式识别、目标检测、图像识别、地球观测以及许多其他研究领域。事实上，机器学习技术及其不可避免的影响在许多国家目前正在推行的诸多技术转型议程中已足够显著，其所带来的益处也十分突出。从区域角度来看，多项研究表明，机器学习技术有助于解决非洲一些最普遍存在的问题，比如减轻贫困、改善教育、提供优质医疗服务，以及应对粮食安全和气候变化等可持续发展挑战。在这篇前沿论文中，我们进行了一项关键的文献计量分析研究，并结合了对机器学习研究的最新进展及相关应用的广泛文献调查，且着眼于非洲。所呈现的文献计量分析研究涵盖了2761篇与机器学习相关的文献，其中89%是文章，这些文章在过去三十年里发表于903种期刊，且至少有482次引用。此外，整理后的文献是从《科学引文索引（扩展版）》中检索而来的，涵盖了1993年至2021年间来自54个非洲国家的研究出版物。该文献计量研究展示了机器学习研究及其应用的当前态势和未来趋势，以促进来自非洲大陆不同研究机构的作者之间未来的合作研究和知识交流。
