Trust and distrust aggregation enhanced with path length incorporation

Authors:
Nele Verbiest;Chris Cornelis;Patricia Victor;Enrique Herrera-Viedma
Affiliations:
Department of Applied Mathematics and Computer Science, Ghent University, Ghent, Belgium;Department of Applied Mathematics and Computer Science, Ghent University, Ghent, Belgium and Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain;Department of Applied Mathematics and Computer Science, Ghent University, Ghent, Belgium;Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain
Venue:
Fuzzy Sets and Systems
Year:
2012

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Abstract

Trust networks are social networks in which users can assign trust scores to each other. In order to estimate these scores for agents that are indirectly connected through the network, a range of trust score aggregators has been proposed. Currently, none of them takes into account the length of the paths that connect users; however, this appears to be a critical factor since longer paths generally contain less reliable information. In this paper, we introduce and evaluate several path length incorporating aggregation strategies in order to strike the right balance between generating more predictions on the one hand and maintaining a high prediction accuracy on the other hand.