Answering Ontological Ranking Queries Based on Subjective Reports

Abstract

The use of preferences in query answering, both in traditional databases and in ontology-based data access, has recently received much attention, due to its many real-world applications. In this paper, we tackle the problem of query answering in Datalog+⁄− ontologies subject to the querying user’s preferences and a collection of subjective reports (i.e., scores for a list of features) of other users, who have their own preferences as well. All these pieces of information are combined to rank the query results. We first focus on the problem of ranking atoms in a database by leveraging reports and customizing their content according to the user’s preferences. Then, we extend this approach to deal with ontological query answering using provenance information. Though the general problem is shown to have an exponential-time data complexity upper bound, we propose a special case that has polynomial time data complexity.