Mining of User Profiles Using Personalized Ontology

To gather useful information from the web has become a challenging issue for users. Current web information gathering systems attempt to satisfy user requirements by capturing their information needs. For this purpose, user profiles are created for user background knowledge description. When representing user profiles many models have utilized only knowledge from either a global analysis or user local information. Through the user profiles, a knowledge representation and reasoning is proposed in this paper. The model constructs user personalized ontologies by extracting global analysis and discovering user background knowledge form user local instance repositories. The proposed ontology model in this paper provides a solution to emphasizing global and local analysis in a single computational model. This ontology model becomes a successful model by evaluating it and it is compared against the benchmark models in web information gathering and also the model has extensive contributions to the fields of Information Retrieval and Information Systems.