Bayesian reputation systems are quite flexible and can relatively easily be adapted to different types of applications and environments. The purpose of this paper is to provide a concise overview of the rich set of features that characterizes Bayesian reputation systems. In particular we demonstrate the importance of base rates during bootstrapping, for handling rating scarcity and for expressing long term trends. © 2009 Springer.

Advanced features in Bayesian reputation systems

Quattrociocchi, Walter
2009-01-01

Abstract

Bayesian reputation systems are quite flexible and can relatively easily be adapted to different types of applications and environments. The purpose of this paper is to provide a concise overview of the rich set of features that characterizes Bayesian reputation systems. In particular we demonstrate the importance of base rates during bootstrapping, for handling rating scarcity and for expressing long term trends. © 2009 Springer.
2009
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/3694075
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