Gestor de Evaluación de Cumplimiento para Proyectos de Investigación Aplicando Redes Complejas y Machine Learning.

Abstract

Management systems have accomplished an important role in the social community over the years. In particular, because of the transition that they have generated on the modeling approach. In software engineering, the modeling of management systems can use decision criteria based on the heuristics. This way several graphical notations that capture the static structures of the system, the behavioral components of the system, and the component is notable of system interactions are practiced. This project is focused on the modeling and development of an expert system to evaluate research projects. Heuristics given by linear regression technique was obtained. Also, activities in projects represented by networks and a degree distribution were obtained to design the evaluation rules. With general parameters of the problem and sample requirements to be evaluated, a model based on the projection of the evaluation was formulated. Thus, statistically weighted parameters were calculated and applied to Scientometrics. Considering those computer systems that consider the evaluation of research activities, it's almost inexistent, this work will improve how research projects will be evaluated.