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Linguistic Consensus Models Based on a Fuzzy Ontology

Ignacio J. Perez, Robin Wikström, József Mezei, Christer Carlsson, Karina Anaya, Enrique Herrera-Viedma, Linguistic Consensus Models Based on a Fuzzy Ontology. In: Yong Shi, Youmin Xi, Peter Wolcott, Yingjie Tian, Jianping Li, Daniel Berg, Zhengxin Chen, E Herrera-Viedmnriquea, Gang Kou, Heeseok Lee, Yi Peng, Lean Yu (Eds.), Proceedings of the First International Conference on Information Technology and Quantitative Management, Procedia Computer Science, 498–505, Elsevier, 2013.

Abstract:

The main purpose of a Group Decision Making model is to reach a consensual solution as quickly as possible by decreasing the gap between the perceptions of different decision makers. The perception of the decision makers depends on the various relations between alternatives and attributes. As a real life example, one can mention the present problem of the euro crisis: before finding a solution for the situation, the different perceptions of each country have to be attuned to have a common ground for negotiations. We have to cope with two different issues when modeling a Group Decision Making problem: (1) the relations describing alternatives and attributes are known only partially in most of the cases and (2) these relations change dynamically. Fuzzy ontologies can provide a solution to handle both issues in an efficient way: we can model incomplete and uncertain information using the well-established theory of fuzzy logic and we can dynamically model the changes in the structure by employing ontologies. Therefore, we propose a new linguistic extension of a consensus model to deal with the psychology of negotiation by using the power of a fuzzy ontology as weapon of influence in order to improve group decision scenarios making them more precise and realistic.

BibTeX entry:

@INPROCEEDINGS{inpPxWiMeCaAnHe13a,
  title = {Linguistic Consensus Models Based on a Fuzzy Ontology},
  booktitle = {Proceedings of the First International Conference on Information Technology and Quantitative Management},
  author = {Perez, Ignacio J. and Wikström, Robin and Mezei, József and Carlsson, Christer and Anaya, Karina and Herrera-Viedma, Enrique},
  series = {Procedia Computer Science},
  editor = {Shi, Yong and Xi, Youmin and Wolcott, Peter and Tian, Yingjie and Li, Jianping and Berg, Daniel and Chen, Zhengxin and Herrera-Viedmnriquea, E and Kou, Gang and Lee, Heeseok and Peng, Yi and Yu, Lean},
  publisher = {Elsevier},
  pages = {498–505},
  year = {2013},
}

Belongs to TUCS Research Unit(s): Institute for Advanced Management Systems Research (IAMSR)

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