Knowledge discovery in distributed databases using evidence theory

Distributed databases allow us to integrate data from different sources which have not previously been combined. The Dempster–Shafer theory of evidence and evidential reasoning are particularly suited to the integration of distributed databases. Evidential functions are suited to represent evidence from different sources. Evidential reasoning is carried out by the well‐known orthogonal sum. Previous work has defined linguistic summaries to discover knowledge by using fuzzy set theory and using evidence theory to define summaries. In this paper we study linguistic summaries and their applications to knowledge discovery in distributed databases. © 2000 John Wiley & Sons, Inc.