Semantic annotation using ontology and Bayesian networks

Abstract

The research presents a semantic annotation framework, named BNOSA. The framework uses ontology to conceptualize a problem domain and uses Bayesian networks to resolve conflicts and to predict missing data. Experiments have been conducted to analyze the performance of the presented semantic annotation framework on different problem domains. The sets of corpuses used in the experiment belong to selling-purchasing websites where product information is entered by ordinary web users. © 2010 Springer-Verlag Berlin Heidelberg.