学术报告第202011期

报告内容：This   report presents an approach to analyze the thematic evolution of a given   research field. This approach combines performance analysis and science   mapping for detecting and visualizing conceptual subdomains (particular   themes or general thematic areas). It allows us to quantify and visualize the   thematic evolution of a given research field. To do this, co-word analysis is   used in a longitudinal framework in order to detect the different themes   treated by the research field across the given time period. The performance   analysis uses different bibliometric measures, including the h-index, with   the purpose of measuring the impact of both the detected themes and thematic   areas. The presented approach includes a visualization method for showing the   thematic evolution of the studied field.

报告人简介：Enrique   Herrera-Viedma    is  Professor in Computer Science and Artificial Intelligence in   University of Granada (UGR) and currently, Vice-President for Research and   Knowlegde Transfer. His current research interests include group   decision making, consensus models, linguistic modeling, aggregation,   information retrieval, bibliometrics, digital libraries, web quality   evaluation,  recommender systems, blockchain and social media. In these   topics he has published more than 300 papers in ISI journals, coordinated   more than 25 research projects, and received more than 35.000 citations   according to Web of Science, being his h-index 83 and 97 in Google Scholar   (see https://scholar.google.com/citations?user=g8ZXTuYAAAAJ&hl=es).   Dr. Herrera-Viedma is Vice-President Publications in IEEE SMC Society, IEEE   FELLOW and an Associate Editor of international journals such  as   the IEEE Trans. On Syst. Man, and Cyb.: Systems, IEEE Trans. On Fuzzy   Systems, IEEE Trans. On Cybernetics, Knowledge Based Systems, Soft Computing,   Fuzzy Optimization and Decision Making, Applied Soft Computing, Journal of   Intelligent and Fuzzy Systems, and Information Sciences. He is identified by   Clarivate Analytics as HIGHLY CITED RESEARCHER in Computer Science and   Engineering from 2014 to 2020 in both categories, “Computer Science” and   “Engineering”.