An Epistemology for Online Information Gathering

As a model for knowledge description and formalization, ontologies are widely used to represent user profiles in personalized web information gathering. However when representing user profiles, many models have utilized only knowledge from either a global knowledge base or user local information. In this paper, a personalized epistemology model is proposed for knowledge representation and reasoning over user profiles. This model learns ontological user profiles from both a world knowledge base and user local instance repositories. The epistemology model is evaluated by comparing it against benchmark models in web information gathering. The results show that this epistemology model is successful.