Web pages Classification Using Domain Ontology and Clustering

Transferring the current Websites to Semantic Websites, using ontology population, is a research area within which classification has the main role. The existing classification algorithms and single level execution of them are insufficient on web data. Moreover, because of the variety in the context and structure of even common domain Websites, there is a lack of training data. In this paper we had three experiences: 1- using information in domain ontology about the layers of classes to train classifiers (layered classification) with improvement up to 10% on accuracy of classification. 2- experience on problem of training dataset and using clustering as a preprocess. 3- using ensembles to benefit from both two methods. Beside the improvement of accuracy from these experiences, we found out that with ensemble we can dispense with the algorithm of classification and use a simple classification like Naïve Bayes and have the accuracy of complex algorithms like SVM.