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Selection criteria for fuzzy unsupervised learning: Applied to market segmentation

  • Germán Sánchez*
  • , N. Agell
  • , Juan Carlos Aguado
  • , Mónica Sánchez
  • , Francesc Prats
  • *Autor/a de correspondencia de este trabajo

Producción científica: Capítulo del libroContribución a congreso/conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

The use of unsupervised fuzzy learning methods produces a large number of alternative classifications. This paper presents and analyzes a series of criteria to select the most suitable of these classifications. Segmenting the clients' portfolio is important in terms of decision-making in marketing because it allows for the discovery of hidden profiles which would not be detected with other methods and it establishes different strategies for each defined segment. In the case included, classifications have been obtained via the LAMDA algorithm. The use of these criteria reduces remarkably the search space and offers a tool to marketing experts in their decision-making.

Idioma originalInglés
Título de la publicación alojadaFoundations of Fuzzy Logic and Soft Computing - 12th International Fuzzy Systems Association World Congress, IFSA 2007, Proceedings
EditorialSpringer Verlag
Páginas307-317
Número de páginas11
ISBN (versión impresa)9783540729174
DOI
EstadoPublicada - 2007
Publicado de forma externa
Evento12th International Fuzzy Systems Association World Congress, IFSA 2007 - Cancun, México
Duración: 18 jun 200721 jun 2007

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen4529 LNAI
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia12th International Fuzzy Systems Association World Congress, IFSA 2007
País/TerritorioMéxico
CiudadCancun
Período18/06/0721/06/07

Huella

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