A group decision making support system for the Web: How to work in environments with a high number of participants and alternatives
Morente-Molinera, Juan Antonio (1)
Pérez, Javier Ignacio
Pérez, Ignacio Javier
Tipo de Ítem:Articulo Revista Indexada
One of the main challenges that the appearance of Web 2.0 and the overall spreading of the Internet have generated is how to tackle with the high number of users and information available. This problem is also inherited by the group decision making problems that can be carried out over the Web. In this article, to solve this issue, a group decision making support system that allows the use of a high number of participants and alternatives is presented. This method allows any number of participants to join the decision making process at any time. Furthermore, they let them provide information only about a certain subset of alternatives. The high participation rate can provide enough information for the decision process to be carried out even if the participants do not provide information about all the high number of available alternatives. (C) 2018 Elsevier B.V. All rights reserved.
Este ítem aparece en la(s) siguiente(s) colección(es)
Mostrando ítems relacionados por Título, autor o materia.
Cabrerizo, Francisco Javier; Morente-Molinera, Juan Antonio (1); Pérez, Ignacio Javier; Urena, Raquel; Herrera-Viedma, Enrique (Aggregation Functions in Theory and in Practice, 2018)A Group decision making process is carried out when human beings jointly make an election from a possible collection of alternatives. Here, a question of importance is to avoid winners and losers, in the sense that the ...
Cabrerizo, Francisco Javier; Morente-Molinera, Juan Antonio (1); Pedrycz, Witold; Taghavi, Atefe; Herrera-Viedma, Enrique (Expert Systems with Applications, 01/07/2018)This study is concerned with group decision making contexts in which linguistic preference relations are used to provide the evaluations of results. On the one hand, granulation of linguistic terms, which are used as entries ...
Improving supervised learning classification methods using multi-granular linguistic modelling and fuzzy entropy Morente-Molinera, Juan Antonio (1); Mezei, Jozsef; Carlsson, Christer; Herrera-Viedma, Enrique (IEEE Transactions on Fuzzy Systems, 10/2017)Obtaining good classification results using supervised learning methods is critical if we want to obtain a high level of precision in the classification processes. The training data used for the learning process plays a ...