AKNOBAS: A Knowledge-based Segmentation Recommender System based on Intelligent Data Mining Techniques Articles uri icon

authors

  • RODRIGUEZ GONZALEZ, ALEJANDRO
  • TORRES NIÑO, JAVIER
  • JIMENEZ DOMINGO, ENRIQUE
  • GOMEZ BERBIS, JUAN MIGUEL
  • ALOR HERNANDEZ, GINER

publication date

  • June 2012

start page

  • 713

end page

  • 740

issue

  • 2

volume

  • 9

International Standard Serial Number (ISSN)

  • 1820-0214

abstract

  • Recommender Systems have recently undergone an unwavering improvement in terms of efficiency and pervasiveness. They have become a source of competitive advantage in many companies which thrive on them as the technological core of their business model. In recent years, we have made substantial progress in those Recommender Systems outperforming the accuracy and added-value of their predecessors, by using cutting-edge techniques such as Data Mining and Segmentation. In this paper, we present AKNOBAS, a Knowledge-based Segmentation Recommender System, which follows that trend using Intelligent Clustering Techniques for Information Systems. The contribution of this Recommender System has been validated through a business scenario implementation proof-of-concept and provides a clear breakthrough of marshaling information through AI techniques.