WSEAS Transactions on Computer Research
Print ISSN: 1991-8755, E-ISSN: 2415-1521
Volume 13, 2025
Methods to Determine the Similarity and Distance between Researchers from Classification Algorithms
Authors: ,
Abstract: In the current era, the scientific and technological production of universities and research institutions is a key factor in advancing knowledge and development. Therefore, having tools to efficiently manage, analyze, and visualize this production becomes essential. However, at the Technical University of Cotopaxi, despite having the Ecuciencia platform to compile this information, there was no efficient method to represent and visualize the similarities and distances between researchers based on their publications and research lines. The main objective of this research is to establish methods based on classification algorithms such as K-means, Spectral Clustering, and Agglomerative Clustering, to determine the similarity and distance between researchers at the university, based on the analysis of their scientific production registered in Ecuciencia, this will allow generating similarity matrices to identify communities of researchers with shared characteristics according to the number of shared publications. This graphical representation will facilitate the analysis of institutional scientific productivity, the detection of patterns, and strategic decision-making regarding research policies. The results obtained will thus strengthen the knowledge management capabilities at the Technical University of Cotopaxi.
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Keywords: Classification Algorithms, Ecuciencia, Similarity, Distance, K-means, Agglomerative, Spectral
Pages: 138-147
DOI: 10.37394/232018.2025.13.14