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Bibliometric analysis of rough sets research
Applied Soft Computing ( IF 8.7 ) Pub Date : 2020-06-12 , DOI: 10.1016/j.asoc.2020.106467
Dejian Yu , Zeshui Xu , Witold Pedrycz

Rough set (RS) is a mathematical framework used to deal with incomplete and uncertain information. It has been widely used in decision analysis, data mining, artificial intelligence, economic management and many other fields. Up to now, there have been tens of thousands of research papers on this topic, and the area has made a rapid growth. In light of these factors, a comprehensive and systematic review of this area becomes essential. The purpose of this study is to present a coherent overview of the theory and applications of the RS, reveal its current research focal points, and identify future development trends. We conduct a thorough bibliometric review and perform co-occurrence and co-citation analysis. First, the fundamental characteristics, productive authors, preferred journals and leading countries in the field of RS are identified. Second, the co-citation and citation burst detection methods are used to explore research hotspot and trends. In light of the undertaken methodology, this study can offer tangible value to scholars in understanding the content structure and development process of the RS field.



中文翻译:

粗糙集研究的文献计量分析

粗糙集(RS)是用于处理不完整和不确定信息的数学框架。它已广泛应用于决策分析,数据挖掘,人工智能,经济管理等许多领域。到目前为止,已经有成千上万的有关该主题的研究论文,并且该领域已经迅速发展。鉴于这些因素,对该领域进行全面而系统的审查至关重要。这项研究的目的是对RS的理论和应用进行连贯的概述,揭示其当前的研究重点,并确定未来的发展趋势。我们进行了详尽的文献计量研究,并进行了同时发生和被引分析。首先,确定RS领域的基本特征,富有成效的作者,首选期刊和领先国家。其次,利用共引和引爆检测方法探索研究热点和趋势。根据所采取的方法论,本研究可以为学者提供了解RS领域的内容结构和发展过程的切实价值。

更新日期:2020-06-12
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