An Ontology-based Approach to Machine Learning and Distributed Knowledge Management

Abstract

This paper proposes a novel approach to knowledge discovery and network adaptation through a high-level ontological and context-based architecture that facilitates information customization and knowledge organization through a longitudinal study of user/network behaviors. The proposed model aims at managing distributed knowledge items through stand-alone computational layers that use ontology to describe and represent knowledge as well as context to adapt knowledge to its hosting environment.