Linguistic-based voting through centered OWA operators

Fuzzy Sets, Rough Sets, Multisets and Clustering

Pérez-Román

2017

Self Cite

In this contribution, we consider that a set of agents assess a set of alternatives through numbers in the unit interval. In this setting, we introduce a measure that assigns a degree of consensus to each subset of agents with respect to every subset of alternatives. This consensus measure is defined as 1 minus the outcome generated by a symmetric aggregation function to the distances between the corresponding individual assessments. We establish some properties of the consensus measure, some of them depending on the used aggregation function. We also introduce an agglomerative hierarchical clustering procedure that is generated by similarity functions based on the previous consensus measures.

Section: Preliminariesmentioning

confidence: 99%

Consensus-Based Agglomerative Hierarchical Clustering

Fuzzy Sets, Rough Sets, Multisets and Clustering

Pérez-Román

2017

Self Cite

“…It is worth pointing out that some authors have shown several paradoxes and inconsistencies of MJ (see Felsenthal and Machover [9], Smith [27], García-Lapresta and Martínez-Panero [12] and Nurmi [22], among others).…”

Section: Majority Judgment Extensionsmentioning

confidence: 99%

“…In order to reduce some of the drawbacks produced by MJ in small committees, García-Lapresta and Martínez-Panero [12] developed a proposal in which the linguistic information is aggregated by means of centered OWA operators (Yager [34]), and a 2-tuple fuzzy linguistic representation (Herrera and Martínez [17]). Another way of thinking was proposed by Zahid [37] who combined MJ with the Borda Count [5] in order to avoid some other inconveniences of MJ.…”

Section: Majority Judgment Extensionsmentioning

confidence: 99%

Allowing agents to be imprecise: A proposal using multiple linguistic terms

Falcó

Roselló

2014

Information Sciences

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In this paper we propose a decision-making procedure where the agents judge the alternatives through linguistic terms such as 'very good', 'good', 'acceptable', etc. If the agents are not confident about their opinions, they can use a linguistic expression formed by several consecutive linguistic terms. To obtain a ranking on the set of alternatives, the method consists of three different stages. The first stage looks for the alternatives in which the overall opinion is closer to the ideal assessment. The overall opinion is developed by a distance-based process among the individual assessments. The next two stages form a tie-breaking process. Firstly by using a dispersion index based on the Gini coefficient, and secondly by taking into account the number of best-assessments. The main characteristics of the proposed decision-making procedure are analyzed.

“…Majority Judgment is a controversial method and some authors have shown several paradoxes and inconsistences (see Smith [22], Felsenthal and Machover [9], García-Lapresta and Martínez-Panero [12] and Nurmi [17], among others).…”

mentioning

confidence: 99%

“…For instance, García-Lapresta and Martínez-Panero [12] proposed an extension for small committees where the linguistic information is aggregated by means of centered OWA operators (Yager [28]) and the 2-tuple fuzzy linguistic representation (Herrera and Martínez [14]). In Falcó and García-Lapresta [7,8], an extension based on the distances between linguistic terms is introduced.…”

mentioning

confidence: 99%

Aggregating Imprecise Linguistic Expressions

Falcó

Human-Centric Decision-Making Models for Social Sciences

Roselló

2013

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In this chapter, we propose a multi-person decision making procedure where agents judge the alternatives through linguistic expressions generated by an ordered finite scale of linguistic terms (for instance, 'very good', 'good', 'acceptable', 'bad', 'very bad'). If the agents are not confident about their opinions, they might use linguistic expressions composed by several consecutive linguistic terms (for instance, 'between acceptable and good'). The procedure we propose is based on distances and it ranks order the alternatives taking into account the linguistic information provided by the agents. The main features and properties of the proposal are analyzed.