A Framework for Knowledge Management on the Semantic Web

The Semantic Web can be a very promising platform for developing knowledge management systems. However, the problem is how to represent knowledge in the machine-understandable form, so that relevant knowledge can be found by machine agents. In this paper we present a knowledge management approach based on RDF-compatible format for representing rules and on a novel technique for the annotation of knowledge sources by using conditional statements. The approach is based on our existing Semantic Web tools. The main benefit is high improvement in the precision by searching for knowledge, as well as the possibility to retrieve a composition of knowledge sources which are relevant for the problem solving.