Visualización de Información mediante mapeo auto-organizado en datos de producción científica de la Universidad Técnica de Cotopaxi.

This research proposal is framed in visualization tools to make decisions and classify scientific documents belonging to research professors at the Technical University of Cotopaxi through self-organized mapping, for which it was necessary to design and develop a methodology that helps to solve the problem presented in the ECUCIENCIA system. At present, neural networks are being investigated for unsupervised learning and decision making, the self-organized mapping methodology (SOM) was designed according to what was proposed by different researchers and experiences during the present investigation. The SOM methodology is structured with a series of phases, from the data load in which there must be a previous analysis and classification for the correct training of the neural network, which results in a data matrix that is subsequently grouped and validated for your viewing. The results obtained can be seen through heat maps, since these express in an interactive and reliable way for the user the visualization of the requested data. Additionally, it is possible to interact with the interface through filters that show the lines and sub-lines of research according to the Technical University of Cotopaxi, the broad, specific and detailed fields according to the CACES and UNESCO and the level of impact on articles according to the category of the magazine in which it was uploaded in which according to the results displayed the researcher will be rewarded.

• Hovedforfatter: Rivera Chasiquiza, Alex Geovanny (author)
• Format: masterThesis
• Sprog: spa
• Udgivet: 2020
• Fag: ECUCIENCIA; MAPAS DE CALOR; REDES NEURONALES ARTIFICIALES; INFORMÁTICA Y SISTEMAS COMPUTACIONALES
• Online adgang: http://repositorio.utc.edu.ec/handle/27000/7233