A Hybrid Approach for Solving the Semantic Annotation Problem in Semantic Social Networks

Abstract

In this paper, we propose a hybrid method that gives a so- lution for the semantic annotation problem. We focus our approach to settle the semantic annotation in social networks. Many approaches use a kind of knowledge representation as taxonomies or ontologies to resolve the annotation problem. Recent works have proposed other probabilistic- based approaches to solve the semantic problem as Bayesian Networks. The nature of the Bayesian learning is given by two phases: the data gathering and the query phase, it can be used to settle the semantic annotation problem viewed as a classication one. This work proposes to combine an ontological approach with a Bayesian learning one applied to give a semantic to publications realized in real time in social networks.