Learning the reasons why groups of consumers prefer some food products

Authors:
Juan José del Coz;Jorge Díez;Antonio Bahamonde;Carlos Sañudo;Matilde Alfonso;Philippe Berge;Eric Dransfield;Costas Stamataris;Demetrios Zygoyiannis;Tyri Valdimarsdottir;Edi Piasentier;Geoffrey Nute;Alan Fisher
Affiliations:
Artificial Intelligence Center, University of Oviedo at Gijón, Gijón, Spain;Artificial Intelligence Center, University of Oviedo at Gijón, Gijón, Spain;Artificial Intelligence Center, University of Oviedo at Gijón, Gijón, Spain;Facultad de Veterinaria, University of Zaragoza, Zaragoza (Aragón), Spain;Facultad de Veterinaria, University of Zaragoza, Zaragoza (Aragón), Spain;Unité de Recherches sur la Viande, wageningen, The Netherlands;Unité de Recherches sur la Viande, wageningen, The Netherlands;Department of Animal Health and Husbandry, Aristotle University, Thessaloniki, Greece;Department of Animal Health and Husbandry, Aristotle University, Thessaloniki, Greece;Icelandic Fisheries Laboratories, Reykjavík, Iceland;Department de Science della Produzione Animale, University of Udinem, Pagnacco, Italy;Department of Food Animal Science, University of Bristol, United Kingdom;Department of Food Animal Science, University of Bristol, United Kingdom
Venue:
ICDM'06 Proceedings of the 6th Industrial Conference on Data Mining conference on Advances in Data Mining: applications in Medicine, Web Mining, Marketing, Image and Signal Mining
Year:
2006

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Abstract

In this paper we propose a method for learning the reasons why groups of consumers prefer some food products instead of others of the same type. We emphasize the role of groups given that, from a practical point of view, they may represent market segments that demand different products. Our method starts representing in a metric space people preferences; there we are able to define similarity functions that allow a clustering algorithm to discover significant groups of consumers with homogeneous tastes. Finally in each cluster, we learn, with a SVM, a function that explains the tastes of the consumers grouped in the cluster. Additionally, a feature selection process highlights the essential properties of food products that have a major influence on their acceptability. To illustrate our method, a real case of consumers of lamb meat was studied. The panel was formed by 773 people of 216 families from 6 European countries. Different tastes between Northern and Southern families were enhanced.