Personalized Composition of Trustful Reputation Systems

Abstract

Abstract. The vast amount of computation techniques for reputation systems proposed in the past has resulted in a need for a global online trust repository with reusable components. In order to increase the practical usability of such a repository, we propose a software framework that supports the user in selecting appropriate components and automatically combines them to a fully functional computation engine. On the one hand, this lets developers experiment with different concepts and move away from one single static computation engine. On the other hand, our software framework also enables an explorative trust evaluation through user interaction. In this way, we notably increase the transparency of reputation systems. To demonstrate the practical applicability of our proposal, we present realistic use cases and describe how it would be employed in these scenarios.

State of the art of reputation-enhanced recommender systems

“…[48]), respectively. The latter actually conflicts with the intuitive assumption that every reputation system comprises exactly one aggregation component, which is also implemented in the software framework on the composition of reputation systems proposed by Sänger et al [42]. In this respect, we propose to conduct some follow-up investigations on the basic classification of reputation systems components as the second future research direction.…”

Interactive Reputation Systems

“…With this in mind, we first decomposed the overall problem to two sub-problems, each addressing one of the two central phases of the generic process of a reputation system: computation and presentation. On the one hand, we elaborated on the question of how the computation could be redesigned as an interactive process (Sänger et al 2015a, c).…”