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Learning the Reasons Why Groups of Consumers Prefer Some Food Products

  • 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
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4065)

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.

Keywords

Cluster Algorithm Food Product Preference Function Ranking Function Market Segment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Juan José del Coz
    • 1
  • Jorge Díez
    • 1
  • Antonio Bahamonde
    • 1
  • Carlos Sañudo
    • 2
  • Matilde Alfonso
    • 2
  • Philippe Berge
    • 3
  • Eric Dransfield
    • 3
  • Costas Stamataris
    • 4
  • Demetrios Zygoyiannis
    • 4
  • Tyri Valdimarsdottir
    • 5
  • Edi Piasentier
    • 6
  • Geoffrey Nute
    • 7
  • Alan Fisher
    • 7
  1. 1.Artificial Intelligence CenterUniversity of Oviedo at GijónGijónSpain
  2. 2.Facultad de VeterinariaUniversity of ZaragozaZaragoza (Aragón)Spain
  3. 3.Unité de Recherches sur la ViandewageningenThe Netherlands
  4. 4.Department of Animal Health and HusbandryAristotle UniversityThessalonikiGreece
  5. 5.Icelandic Fisheries LaboratoriesReykjavíkIceland
  6. 6.Department de Science della Produzione AnimaleUniversity of UdinemPagnaccoItaly
  7. 7.Department of Food Animal ScienceUniversity of BristolUnited Kingdom

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