GDM-VieweR: A New Tool in R to Visualize the Evolution of Fuzzy Consensus Processes

  • Raquel Ureña
  • Francisco Javier Cabrerizo
  • Francisco Chiclana
  • Enrique Herrera-Viedma
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 532)


With the incorporation of web 2.0 frameworks the complexity of decision making situations has exponentially increased, involving in many cases many experts, and a pontentially huge number of different alternatives. In the literature we can find a great deal of methodologies to assist multi-person decision making. However these classical approaches are not prepared to deal with huge complexity environments such as the Web 2.0, and there is a lack of tools that support the decision processes providing some graphical information. In this context is where data visualizations plays a key role. Therefore the main objective of this contribution is to present an open source tool developed in R to provide a quick insight of the evolution of the decision making by means of meaningful graphical representations. These tools allows its users to convey ideas effectively, providing insights into a rather sparse and complex data set by communicating its key-aspects in a more intuitive way and contributiong to the decision maker engangement in the process.


Group decision making Fuzzy preference modeling Software development 



The authors would like to acknowledge FEDER financial support from the Project TIN2013-40658-P, and also the financial support from the Andalusian Excellence Project TIC-5991.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Raquel Ureña
    • 1
  • Francisco Javier Cabrerizo
    • 2
  • Francisco Chiclana
    • 3
  • Enrique Herrera-Viedma
    • 1
  1. 1.Department of Computer Science and A.IUniversity of GranadaGranadaSpain
  2. 2.Department of Software Engineering and Computer SystemsUniversidad Nacional de Educación a Distancia (UNED)MadridSpain
  3. 3.Centre for Computational Intelligence, Faculty of TechnologyDe Montfort UniversityLeicesterUK

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