A Personalized Ontology Mining for Web Information Retrieval

Ontology is a formal description and specification of knowledge. Information systems are expected to be able to understand the semantic meaning of words and phrases, and be able to compare information items by concepts instead of keywords by using ontology models. In this project, a personalized ontology model is proposed, that learns ontological user profiles from both world knowledge base and user local instance repositories. Hence user background knowledge can be better discovered and represented while integrating global and local analysis within a hybrid model. This ontology model will be compared with several benchmark models and will be evaluated how it is successful in acquiring user required information. This project also extends the study on ontological mapping that will improve the performance of personalized user profiles.