ELM Predicting Trust from Reputation in a Social Network of Reviewers

  • J. David Nuñez-Gonzalez
  • Manuel Graña
Part of the Adaptation, Learning, and Optimization book series (ALO, volume 16)


Trust is a central concept in distributed systems, such as Ad Hoc Networks, Social Networks and Recommender Systems. Trust has a predictive component, it is a measure of the certainty that an agent has on the output from other agent. Hence, Trust is a key component of distributed decision making processes. It can be built from reputation, meaning the observation of the Trust values from other agents (the trusters) on the target agent (the trustee). In this chapter we take the point of view of predicting the Trust value on the basis of the reputation information that the agent may collect. When Trust values are categorical, or binary, the problem becomes a classification problem that can be tackled by Extreme Learning Machines (ELM). We perform experimental assessment of the value of ELM for this task on a benchmark database obtained from a real life recommender system.


ELM Trust computation Recommender systems 



This research has been partially funded by EU through SandS project, grant agreement No. 317947.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Computational Intelligence GroupUniversity of the Basque CountryUPV/EHUSpain

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