Please use this identifier to cite or link to this item:
Rough Sets: A Bibliometric Analysis from 2014 to 2018
|Title:||Rough Sets: A Bibliometric Analysis from 2014 to 2018|
Moral-Muñoz, Jose A.
Cobo, Manuel J.
|Keywords:||Soft Computing: Theory Innovations and Problem Solving Benefits|
|Date Issued:||07 Jan 2020|
|Abstract:||Along almost forty years, considerable research has been undertaken on rough set theory to deal with vague information. Rough sets have proven to be extremely helpful for a diversity of computer-science problems (e.g., knowledge discovery, computational logic, machine learning, etc.), and numerous application domains (e.g., business economics, telecommunications, neurosciences, etc.). Accordingly, the literature on rough sets has grown without ceasing, and nowadays it is immense. This paper provides a comprehensive overview of the research published for the last five years. To do so, it analyzes 4,038 records retrieved from the Clarivate Web of Science database, identifying (i) the most prolific authors and their collaboration networks, (ii) the countries and organizations that are leading research on rough sets, (iii) the journals that are publishing most papers, (iv) the topics that are being most researched, and (v) the principal application domains.|
|Rights:||Attribution-NonCommercial-NoDerivatives 4.0 International|
|Appears in Collections:||
Soft Computing: Theory Innovations and Problem Solving Benefits|
Please email firstname.lastname@example.org if you need this content in ADA-compliant format.
This item is licensed under a Creative Commons License