dc.contributor.author | Hussain, Syed Sajjad | |
dc.date.accessioned | 2011-04-12T11:47:10Z | |
dc.date.available | 2011-04-12T11:47:10Z | |
dc.date.issued | 2011-04-12 | |
dc.identifier.uri | http://hdl.handle.net/10222/13350 | |
dc.description.abstract | Knowledge-driven problem solving demands 'complete' knowledge about the domain and its interpretation under different contexts. Knowledge Morphing aims at a context-driven integration of heterogeneous knowledge sources--in order to provide a comprehensive and networked view of all knowledge about a domain-specific problem, pertaining to the context at hand. In this PhD thesis, we have proposed a Semantic Web based framework, K-MORPH, for Knowledge Morphing via Reconciliation of Contextualized Sub-ontologies. In order to realize our K-MORPH framework, we have developed: (i) a sub-ontology extraction method for generating contextualized sub-ontologies from the source ontologies pertinent to the problem-context at hand; (ii) two ontology matching approaches: triple-based ontology matching (TOM) and proof-based ontology matching (POM) for finding both atomic and complex correspondences between two extracted contextualized sub-ontologies; and (iii) our approach for resolving inconsistencies in ontologies by generating minimal inconsistent resolve candidates (MIRCs), where removing any of the MIRCs from the inconsistent ontology results in a maximal consistent sub-ontology. Thus, K-MORPH performs knowledge morphing among ontology-modelled knowledge sources and generates a context-sensitive and comprehensive knowledge-base pertinent to the problem at hand by (a) extracting problem-specific knowledge components from ontology-modelled knowledge sources using our sub-ontology extraction method; (b) aligning and merging the extracted knowledge components using our matching approaches; and (c) repairing inconsistencies in the morphed knowledge by applying our approach for detecting and resolving inconsistencies. We demonstrated the application of our K-MORPH framework in the healthcare domain, where K-MORPH generated a merged ontology for providing a comprehensive therapeutic knowledge-base for Urinary Tract Infections (UTI) by first (i) extracting 20 contextualized sub-ontologies from various UTI ontologies of different healthcare institutions, (ii) aligning and merging the extracted UTI sub-ontologies, and (iii) detecting and resolving inconsistencies in the merged UTI ontology. | en_US |
dc.language.iso | en | en_US |
dc.subject | Knowledge Management | en_US |
dc.subject | Knowledge Integration | en_US |
dc.subject | Semantic Web | en_US |
dc.subject | Ontology Modularization | en_US |
dc.subject | Ontology Matching | en_US |
dc.subject | Ontology Debugging | en_US |
dc.title | K-MORPH: Knowledge Morphing via Reconciliation of Contextualized Sub-ontologies | en_US |
dc.date.defence | 2011-03-29 | |
dc.contributor.department | Faculty of Computer Science | en_US |
dc.contributor.degree | Doctor of Philosophy | en_US |
dc.contributor.external-examiner | Dr. Mor Peleg | en_US |
dc.contributor.graduate-coordinator | Dr. Malcom Heywood | en_US |
dc.contributor.thesis-reader | Dr. Michael Shepherd | en_US |
dc.contributor.thesis-reader | Dr. Denis Riordan | en_US |
dc.contributor.thesis-supervisor | Dr. Syed Sibte Raza Abidi | en_US |
dc.contributor.ethics-approval | Not Applicable | en_US |
dc.contributor.manuscripts | Not Applicable | en_US |
dc.contributor.copyright-release | Not Applicable | en_US |