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Applied Intelligence

, Volume 40, Issue 1, pp 127–142 | Cite as

Strategies for avoiding preference profiling in agent-based e-commerce environments

  • Emilio SerranoEmail author
  • Jose M. Such
  • Juan A. Botía
  • Ana García-Fornes
Article

Abstract

Agent-based electronic commerce is known to offer many advantages to users. However, very few studies have been devoted to deal with privacy issues in this domain. Privacy is of great concern and preserving users’ privacy plays a crucial role to promote their trust in agent-based technologies. In this paper, we focus on preference profiling, which is a well-known threat to users’ privacy. Specifically, we review strategies for customers’ agents to prevent seller agents from obtaining accurate preference profiles of the former group by using data mining techniques. We experimentally show the efficacy of each of these strategies and discuss their suitability in different situations. Our experimental results show that customers can improve their privacy notably with these strategies.

Keywords

Privacy Agent-based e-commerce Preference profiling Interaction analysis Data mining 

Notes

Acknowledgements

This research work is supported by the Spanish Ministry of Science and Innovation in the scope of the Research Projects TSI-020302-2010-129, TIN2011-28335-C02-02 and through the Fundación Séneca within the Program 04552/GERM/06.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Emilio Serrano
    • 1
    Email author
  • Jose M. Such
    • 2
  • Juan A. Botía
    • 3
  • Ana García-Fornes
    • 4
  1. 1.Polytechnic University of MadridMadridSpain
  2. 2.Lancaster UniversityLancasterUK
  3. 3.University of MurciaMurciaSpain
  4. 4.Polytechnic University of ValenciaValènciaSpain

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