Tractable approximate deduction for OWL

Acknowledgements This work has been partially supported by the European project Marrying Ontologies and Software Technologies (EU ICT2008-216691), the European project Knowledge Driven Data Exploitation (EU FP7/IAPP2011-286348), the UK EPSRC project WhatIf (EP/J014354/1). The authors thank Prof. Ian Horrocks and Dr. Giorgos Stoilos for their helpful discussion on role subsumptions. The authors thank Rafael S. Gonçalves et al. for providing their hotspots ontologies. The authors also thank BoC-group for providing their ADOxx Metamodelling ontologies.Peer reviewedPostprin

Approximate Assertional Reasoning Over Expressive Ontologies

In this thesis, approximate reasoning methods for scalable assertional reasoning are provided whose computational properties can be established in a well-understood way, namely in terms of soundness and completeness, and whose quality can be analyzed in terms of statistical measurements, namely recall and precision. The basic idea of these approximate reasoning methods is to speed up reasoning by trading off the quality of reasoning results against increased speed

Approximating Terminological Queries

Current proposals for languages to encode terminological knowledge in intelligent systems support logical reasoning for answering user queries about objects and classes. An application of these languages on the World Wide Web, however, is hampered by the limitations of logical reasoning in terms of e#ciency and flexibility. In this paper we describe, how techniques from approximate reasoning can be used to overcome these problems. We discuss terminological knowledge and approximate reasoning in general and show the benefits of approximate reasoning using the example of building and maintaining semantic catalogues that can be used to query resource locations based on object classes