Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Transferring the current bsites to Semantic bsites, 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 b data. Moreover, because of the variety in the context and structure of even common domain bsites, there is a lack of training data.   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,  found out that with ensemble  can dispense with the algorithm of classification and use a simple classification like Naive Bayes and have the accuracy of complex algorithms like SVM.
['Sima Soltani', 'Ahmad Abdollahzadeh Barforoush']
I am writing a research paper on a idea Web pages Classification Using Domain Ontology and Clustering
[{"from": "human", "value": "I am writing a research paper on a idea Web pages Classification Using Domain Ontology and Clustering"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Transferring the current bsites to Semantic bsites, 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 b data. Moreover, because of the variety in the context and structure of even common domain bsites, there is a lack of training data.   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,  found out that with ensemble  can dispense with the algorithm of classification and use a simple classification like Naive Bayes and have the accuracy of complex algorithms like SVM."}]