Delphosuna aplicación para la ayuda a la toma de decisiones de las empresas basada en procesos de inteligencia competitiva y apoyada en algoritmos genéticos para la mejora de consultas

  1. Tena Mateos, María José
Dirigée par:
  1. Antonio Muñoz Cañavate Directeur/trice
  2. María Cristina López Pujalte Co-directeur/trice

Université de défendre: Universidad de Extremadura

Fecha de defensa: 26 novembre 2019

Jury:
  1. Rosario Arquero Avilés President
  2. María Carmen Solano Macías Secrétaire
  3. Pedro Hípola Ruiz Rapporteur

Type: Thèses

Résumé

Current companies are faced with the need for new methods and tools for information management that allow them to survive and prosper in a highly competitive environment where uncertainty and ambition are the norm. Two of the most prominent strategies that take information and its treatment as a generating element of value in the decision-making of companies are Technology Monitoring and Competitive Intelligence. In addition, one of the fundamental components with the obligations must have a system based on these disciplines is an efficient information retrieval methodology. In recent years, one of the main research changes in information retrieval has been configured by Genetic Algorithms, a practice within the field of Artificial Intelligence. His research has allowed us to develop an algorithm with which to achieve a greater understanding of how they can contribute to the improvement of information retrieval through query optimization and how the results can be applied, in turn, on tools that generate knowledge for organizations