DL-based ontologies have been widely used as knowledge infrastructures in knowledge management systems and on the Semantic Web. The development of efficient, sound and complete reasoning technologies has been a central topic in DL research. Recently, the paradigm shift from professional to novice users, and from standalone and static to inter-linked and dynamic applications raises new challenges: Can users build and evolve ontologies, both static and dynamic, with features provided by expressive DLs, while still enjoying e cient reasoning as in tractable DLs, without worrying too much about the quality (soundness and completeness) of results? To answer these challenges, this thesis investigates the problem of tractable and quality-guaranteed reasoning for ontologies in expressive DLs. The thesis develops syntactic approximation, a consequence-based reasoning procedure with worst-case PTime complexity, theoretically sound and empirically high-recall results, for ontologies constructed in DLs more expressive than any tractable DL. The thesis shows that a set of semantic completeness-guarantee conditions can be identifed to efficiently check if such a procedure is complete. Many ontologies tested in the thesis, including difficult ones for an off-the-shelf reasoner, satisfy such conditions. Furthermore, the thesis presents a stream reasoning mechanism to update reasoning results on dynamic ontologies without complete re-computation. Such a mechanism implements the Delete-and-Re-derive strategy with a truth maintenance system, and can help to reduce unnecessary over-deletion and re-derivation in stream reasoning and to improve its efficiency. As a whole, the thesis develops a worst-case tractable, guaranteed sound, conditionally complete and empirically high-recall reasoning solution for both static and dynamic ontologies in expressive DLs. Some techniques presented in the thesis can also be used to improve the performance and/or completeness of other existing reasoning solutions. The results can further be generalised and extended to support a wider range of knowledge representation formalisms, especially when a consequence-based algorithm is available.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:633293 |
| Date | January 2014 |
| Creators | Ren, Yuan |
| Publisher | University of Aberdeen |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=217884 |
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