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Title: Application of a text analytics model for the automatic discovery and classification of research trends in e-learning (the UOC case)
Author: López Ruiz, José
Garcia Brustenga, Guillem
Others: Universitat Oberta de Catalunya. eLearn Center (eLC)
Keywords: text mining
scientific literature
research tasks
bibliographical references
online university
Issue Date: 25-Nov-2019
Publisher: Universitat Oberta de Catalunya (UOC)
Abstract: The review of scientific literature is a common task among researchers who wish to detect the trends that are influencing the evolution of a discipline or specific field of research. Obtaining such knowledge requires heavy and repetitive tasks of extraction, analysis, synthesis and classification of hundreds, and in some cases thousands, of bibliographic references. These first phases require a great effort on the part of the team of analysts to collect and order the results of the scientific evidence on which to base their conclusions, dedication that can be increased depending on the zoom of each search. In its capacity to observe the "world map" of knowledge to detect and reflect on the trends and events that are transforming online higher education in the world, the eLC integrates into its activity such tasks of documental review and prospective. With the intention of facilitating the path towards the discovery and analysis of the relevant objective information of each study, the centre has piloted a project consisting of automating part of this revision process based on the use of analytical technologies and text mining.
Language: English
ISBN: 978-84-09-17132-3
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