Idempotent linearly compensated hybrid connectives for customers patterns segmentation

Núria Agell Jané, Catalina Olmo Olmo, Francesc Prats Duaygues, German Sánchez Hernández, Mònica Sánchez Soler

Producció científica: Contribució a una conferènciaContribució

Resum

Abstract. When employing unsupervised learning methods to auto- matically generate segmentations from the available data, often a lot of alternative segmentations are produced. In this paper the unsuper- vised learning capability of LAMDA (Learning Algorithm for Multivari- ate Data Analysis) algorithm is applied and the results are intended to help marketing experts to ¯nd out hidden patterns among their cus- tomers pro¯les. LAMDA algorithm, uses hybrid linearly compensated connectives in the learning process. The condition of idempotence imposed to the hybrid connectives reduces the space of search and guaranties coherence in the obtained segmentation. The obtained results are applied to identify the behaviour and needs of the customers of a Spanish retailer.
Idioma originalAnglès
Estat de la publicacióPublicada - 14 de nov. 2005
EsdevenimentConferencia de la Asociación Española para la Inteligencia Artificial, Santiago de Compostela 2005 -
Durada: 14 de nov. 200518 de nov. 2005

Conferència

ConferènciaConferencia de la Asociación Española para la Inteligencia Artificial, Santiago de Compostela 2005
Període14/11/0518/11/05

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