Efforts to blend ontology with Bayesian networks: An overview

Abstract

The concept of ontology modeling and engineering has drastically evolved with the emergence of semantic web. Today in a collaborative environment ontologies need to interoperate for efficient data exchange. Due to their deterministic nature, ontologies are unable to capture uncertainty inherent in many real world problems. Efforts have been made to add the dimension of uncertainty by synergizing Bayesian network with ontology - a combination in which domain knowledge and probabilistic information go hand in hand. This paper categorizes different approaches that have been proposed to blend ontology and Bayesian networks. It also discusses the scope of these approaches and their intended application areas. Their relative strengths and weaknesses are also highlighted. The paper contributes significantly by providing a comprehensive comparison which could serve as the starting point for new researchers.