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Title: Foundations and applications of knowledge representation for structured entities
Author: Magka, Despoina
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2013
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Description Logics form a family of powerful ontology languages widely used by academics and industry experts to capture and intelligently manage knowledge about the world. A key advantage of Description Logics is their amenability to automated reasoning that enables the deduction of knowledge that has not been explicitly stated. However, in order to ensure decidability of automated reasoning algorithms, suitable restrictions are usually enforced on the shape of structures that are expressible using Description Logics. As a consequence, Description Logics fall short of expressive power when it comes to representing cyclic structures, which abound in life sciences and other disciplines. The objective of this thesis is to explore ontology languages that are better suited for the representation of structured objects. It is suggested that an alternative approach which relies on nonmonotonic existential rules can provide a promising candidate for modelling such domains. To this end, we have built a comprehensive theoretical and practical framework for the representation of structured entities along with a surface syntax designed to allow the creation of ontological descriptions in an intuitive way. Our formalism is based on nonmonotonic existential rules and exhibits a favourable balance between expressive power and computational as well as empirical tractability. In order to ensure decidability of reasoning, we introduce a number of acyclicity criteria that strictly generalise many of the existing ones. We also present a novel stratification condition that properly extends `classical' stratification and allows for capturing both definitional and conditional aspects of complex structures. The applicability of our formalism is supported by a prototypical implementation, which is based on an off-the-shelf answer set solver and is tested over a realistic knowledge base. Our experimental results demonstrate improvement of up to three orders of magnitude in comparison with previous evaluation efforts and also expose numerous modelling errors of a manually curated biochemical knowledge base. Overall, we believe that our work lays the practical and theoretical foundations of an ontology language that is well-suited for the representation of structured objects. From a modelling point of view, our approach could stimulate the adoption of a different and expressive reasoning paradigm for which robustly engineered mature reasoners are available; it could thus pave the way for the representation of a broader spectrum of knowledge. At the same time, our theoretical contributions reveal useful insights into logic-based knowledge representation and reasoning. Therefore, our results should be of value to ontology engineers and knowledge representation researchers alike.
Supervisor: Horrocks, Ian; Krötzsch, Markus; Motik, Boris Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Bioinformatics (life sciences) ; Artificial Intelligence ; Computer science (mathematics) ; Logic ; Applications and algorithms ; Knowledge representation and reasoning ; semantic technologies ; cheminformatics ; computational complexity ; decidability ; classification ; ontology