Agell, N.; van Ganzewinkel,, C.; Sanchez, M.; Rosello, L.; Prats, F.; Andriessen, P. Applied soft computing Vol. 35, p. 942-948 DOI: 10.1016/j.asoc.2015.03.024 Date of publication: 2015-10 Journal article
This paper proposes a new model of consensus based on linguistic terms to be implemented in Delphi processes. The model of consensus involves qualitative reasoning techniques and is based on the concept of entropy. The proposed model has the ability to reach consensus automatically without the need for either a moderator or a final interaction among panelists. In addition, it permits panelists to answer with different levels of precision depending on their knowledge on each question. The model defined hasbeen used to establish the relevant features for the definition of a type of chronic disease. A real-case application conducted in the Department of Neonatology of Máxima Medical Center in The Netherlands is presented. This application considers the opinions of stakeholders of neonate health-care in order toreach a final consensual definition of chronic pain in neonates.
Agell, N.; van Ganzewinkel,, C.; Sanchez, M.; Rosello, L.; Prats, F.; Andriessen, P. IEEE International Conference on Fuzzy Systems p. 5-10 DOI: 10.1109/FUZZ-IEEE.2014.6891645 Presentation's date: 2014-07-07 Presentation of work at congresses
A new approach for Delphi processes including a
measure of consensus based on linguistic terms is introduced in this paper. The measure of consensus involves qualitative reasoning techniques and is based on the concept of entropy. In the proposed approach, consensus is reached automatically
without the need for neither a moderator nor a final interaction among panelists. In addition, it permits panelists to answer with different levels of precision depending on their knowledge on each question. An illustrative example considering the opinions of stake holders in neonate health-care to reach a final
consensual definition of chronic pain in neonates is presented.
We formally construct the extended set of qualitative labels Lover a well-ordered set.The qualitative descriptions of a given set are defined as L-fuzzy sets. In the case where the well-ordered set is finite, a distance between L-fuzzy sets is introduced based on the properties of the lattice L. The concept of the information contained in a qualitative label is introduced, leading to a formal definition of the entropy of an L-fuzzy set as a Lebesgue integral. In the discrete case, this integral becomes a weighted average of the information of the labels, corresponding to the Shannon entropy in information theory.
This paper presents a new approach based upon qualitative reasoning techniques for representing and synthesising the information given by a group of evaluators. A mathematical formulation is developed that contributes to decision-making analysis in the context of multi-attribute and group decision-making. This method, is applied in choice and ranking problems and can work at different precision levels. To represent non-trivial domain knowledge, the patterns or alternatives to be ranked are characterised by a set of features, which are evaluated by each member of the group through linguistic labels corresponding to ordinal values. Different levels of precision are considered to draw the distinctions required by evaluators’ reasoning processes. The method used for ranking alternatives is based on comparing distances against an optimal reference point. A theorem on the consistency of the proposed method is presented and proved. Three real-life applications are presented to outline areas of management where the proposed method has been implemented and achieved interesting results.
Rosello, L.; Sanchez, M.; Agell, N.; Prats, F. International Conference of the Catalan Association for Artificial Intelligence p. 173-182 Presentation's date: 2010-10-22 Presentation of work at congresses
This paper presents the foundation for a new methodology for a collaborative recommender system (RS). This methodology is based on the degree of consensus of a group of users
stating their preferences via qualitative orders-of-magnitude.
The structure of distributive lattice is considered in defining the distance between users and the RSs new users. This proposed
methodology incorporates incomplete or partial knowledge into the recommendation process using qualitative reasoning techniques to obtain consensus of its users for recommendations.
This paper presents a mathematical framework to assess the consensus found among different evaluators who use ordinal scales in group decision-making and evaluation
processes. This framework is developed on the basis of the absolute order-of-magnitude
qualitative model through the use of qualitative entropy. As such, we study the algebraic structure induced in the set of qualitative descriptions given by evaluators. Our results demonstrate a weak, partial and semi lattice structure that in some conditions takes the form of a distributive lattice. We then define the entropy of a qualitatively-described system.
This enables us, on the one hand, to measure the amount of information provided by each
evaluator and, on the other hand, to consider a degree of consensus among the evaluation committee. This new approach is capable of managing situations where the assessment given by experts involves different levels of precision. In addition, when there is no consensus regarding the group decision, an automatic process assesses the effort required to achieve
Ordinal scales are commonly used in rating and evaluation processes. These processes usually involve group decision making by means of an experts’ committee. In this paper a mathematical framework based on the qualitative model of the absolute orders of magnitude is considered. The entropy of a qualitatively described system is defined in this framework.
On the one hand, this enables us to measure the amount of information provided by each evaluator and, on the other hand, the coherence of the evaluation committee. The new approach is capable of managing situations where the assessment given by experts involves different levels of precision.
The use of the proposed measures within an automatic system for group decision making will contribute towards avoiding the potential subjectivity caused by conflicts of interests of the evaluators in the group.