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Trust and Recommendations

  • Patricia Victor
  • Martine De Cock
  • Chris Cornelis
Chapter

Abstract

Recommendation technologies and trust metrics constitute the two pillars of trust-enhanced recommender systems. We discuss and illustrate the basic trust concepts such as trust and distrust modeling, propagation and aggregation. These concepts are needed to fully grasp the rationale behind the trust-enhanced recommender techniques that are discussed in the central part of the chapter, which focuses on the application of trust metrics and their operators in recommender systems. We explain the benefits of using trust in recommender algorithms and give an overview of state-of-the-art approaches for trust-enhanced recommender systems. Furthermore, we explain the details of three well-known trust-based systems and provide a comparative analysis of their performance. We conclude with a discussion of some recent developments and open challenges, such as visualizing trust relationships in a recommender system, alleviating the cold start problem in a trust network of a recommender system, studying the effect of involving distrust in the recommendation process, and investigating the potential of other types of social relationships.

Keywords

Root Mean Square Error Recommender System Trust Propagation Target User Trust Network 
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 Science+Business Media, LLC 2011

Authors and Affiliations

  • Patricia Victor
    • 1
  • Martine De Cock
    • 2
  • Chris Cornelis
    • 1
  1. 1.Dept. of Applied Mathematics and Computer ScienceGhent UniversityGentBelgium
  2. 2.Institute of Technology, University of Washington TacomaTacomaUSA

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