Scientometric analysis of research trends in clustering and nature inspired techniques
Shruti Aggarwal, Amit Verma · AIP conference proceedings · 2022
Nature inspired techniques are most popular techniques used for optimization. Clustering is a data mining functionality which is also used in optimization. In recent past, researchers have implemented several nature inspired techniques using clustering. In this paper, scientometric analysis is conducted to analyze the research trends of these techniques using data from Web of Science and Scopus databases where analysis of ACO, PSO, Bat, Lion, water droplets, and such optimization techniques inspired by nature are studies which use k-means, DB Scan, k-neighbor and other such clustering algorithms. Data is analyzed globally, cluster analysis of related keywords in analyzed along with link strength. Various other experiments are also conducted which help analyze research trends in clustering and nature inspired techniques.