Research in Computing Science, Vol. 65, pp. 25-33, 2013.
Abstract: In this paper, we propose a hybrid method that gives a solution 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 classification 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.
Keywords: Semantic annotation, social networks.
PDF: A Hybrid Approach for Solving the Semantic Annotation Problem in Semantic Social Networks
PDF: A Hybrid Approach for Solving the Semantic Annotation Problem in Semantic Social Networks