A highly adaptive recommender system based on fuzzy logic for B2C e-commerce portals

  • Authors:
  • Jose Jesus Castro-Schez;Raul Miguel;David Vallejo;Lorenzo Manuel López-López

  • Affiliations:
  • Escuela Superior de Informatica, University of Castilla-La Mancha, Paseo de la Universidad 4, Ciudad Real 13071, Spain;Escuela Superior de Informatica, University of Castilla-La Mancha, Paseo de la Universidad 4, Ciudad Real 13071, Spain;Escuela Superior de Informatica, University of Castilla-La Mancha, Paseo de la Universidad 4, Ciudad Real 13071, Spain;Escuela Superior de Informatica, University of Castilla-La Mancha, Paseo de la Universidad 4, Ciudad Real 13071, Spain

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2011

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Abstract

Past years have witnessed a growing interest in e-commerce as a strategy for improving business. Several paradigms have arisen from the e-commerce field in recent years which try to support different business activities, such as B2C and C2C. This paper introduces a prototype of e-commerce portal, called e-Zoco, of which main features are: (i) a catalogue service intended to arrange product categories hierarchically and describe them through sets of attributes, (ii) a product selection service able to deal with imprecise and vague search preferences which returns a set of results clustered in accordance with their potential relevance to the user, and (iii) a rule-based knowledge learning service to provide the users with knowledge about the existing relationships among the attributes that describe a given product category. The portal prototype is supported by a multi-agent infrastructure composed of a set of agents responsible for providing these and other services.