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Filtering Out Unfair Recommendations for Trust Model in Ubiquitous Environments

  • Weiwei Yuan
  • Donghai Guan
  • Sungyoung Lee
  • Young-Koo Lee
  • Heejo Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4332)

Abstract

This paper presents a novel context-based approach to filter out unfair recommendations for trust model in ubiquitous environments. Context is used in our approach to analyze the user’s activity, state and intention. Incremental learning based neural network is used to dispose the context in order to find doubtful recommendations. This approach has distinct advantages when dealing with randomly given irresponsible recommendations, individual unfair recommendations as well as unfair recommendations flooding.

Keywords

Trust Model Ubiquitous Computing Hide Unit Malicious Node Incremental Learning 
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

  • Weiwei Yuan
    • 1
  • Donghai Guan
    • 1
  • Sungyoung Lee
    • 1
  • Young-Koo Lee
    • 1
  • Heejo Lee
    • 2
  1. 1.Department of Computer EngineeringKyung Hee UniversityKorea
  2. 2.Department of Computer Science and EngineeringKorea University 

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