Knowledge engineering method based on consensual knowledge and trust computation: The MUSCKA system

Abstract

We propose a method for building a knowledge base addressing specific issues such as covering end-users’ needs. After designing an ontology module representing the knowledge needed, we enrich and populate it automatically with knowledge extracted from existing sources such as thesauri or classifications. The originality of our proposition is to propose ontological object candidates from existing sources according to their relatedness to the ontological module and to their trust score. This paper describes the trust measures we propose which are obtained by analysing the consensus found in existing sources. We consider that knowledge is more reliable if it has been extracted from several sources. Our measures has been evaluated on a real case study with experts from the agriculture domain.