Concepts for Trust Propagation in Knowledge Processing Systems - A Brief Introduction and Overview

Abstract

What is Trust? Everybody has a sense of trusting people or institutions, but how is trust defined? The definition of trust always depends on the specific field of research and application, which makes it hard to answer this question in general at a computational level. Thinking of knowledge processing systems we face this question twice. How can we define and calculate trust values for the input data and, more challenging, what is the trust value of the output? Within this paper we consider a binary, a probabilistic, an opinion-space and - our recently developed approach - a weighted arithmetic mean trust model. Then we show ways, how knowledge processing systems can handle these trust values and propagate them through a network of processing steps in a way that the final results are representative. With these presented and developed models, we can give insights to the topic of defining and propagating trust in knowledge processing systems.