Abstract:
This paper presents a technical approach for
fusing information from diverse sources. Fusion requires
appropriate weighting of information based on the
quality of the source of the information. A credibility
model characterizes the quality of information based on
the source and the circumstances under which the
information is collected. In many cases credibility is
uncertain, so inference is necessary. Explicit
probabilistic credibility models provide a computational
model of the quality of the information that allows use of
prior information, evidence when available, and
opportunities for learning from data. This paper
provides an overview of the challenges, describes the
advanced probabilistic reasoning tools used to implement
credibility models, and provides an example of the use of
credibility models in a multi-source fusion process.
