Título
A new preference classification approach: The λ-dissensus cluster algorithm
Autor(es)
Palabras clave
Preferences
Weak orders
Preference grouping
Preference cohesion
Clustering for orders vectors
Clasificación UNESCO
Fecha de publicación
2022
Editor
Elsevier
Citación
Cascón, J. M., González-Arteaga, T., & De Andrés Calle, R. (2022). A new preference classification approach: The λ -dissensus cluster algorithm. Omega, 111, 102663. https://doi.org/10.1016/j.omega.2022.102663
Resumen
[EN] Preferences and their classification are essential in many decision making processes. However, grouping
preferences is not an easy matter because their very nature. In this paper a new preference clustering
algorithm is proposed that incorporates the key features of preferences, usually represented by order
vectors, and it takes ideas from Social Choice Theory, Decision Making Theory and Cluster Analysis as
sources of inspiration. Additionally, a study of the main properties of our proposal is included as well as
several internal validation measurements. Finally and in order to improve understanding of the proposed
approach, assorted experiments on real data are included.
URI
ISSN
0305-0483
DOI
10.1016/j.omega.2022.102663
Versión del editor
Aparece en las colecciones
Patrocinador
Publicación en abierto financiada por la Universidad de Salamanca como participante en el Acuerdo Transformativo CRUE-CSIC con Elsevier, 2021-2024
