Comparing Instances of Ontological Concepts for Personalized Recommendation in Large Information Spaces

Abstract

We present a novel method for instance comparison of ontological concepts with regard to personalized content presentation and/or navigation in large information spaces. We assume that comparing properties of documents which users found interesting leads to discovery of information about users' interests specifically when considering Semantic Web applications where documents or their parts are represented by ontological concepts. We employ the ontology structure and different similarity metrics for datatype and object properties and investigate reasons behind user interest in the presented content. Moreover, we propose and evaluate an approach to instance similarity computation for a particular user while also considering the user's individual preferences.