Iterative Ontology Update with Minimum Change

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Iterative Ontology Update with Minimum Change

Masterarbeit von Aparna Saisree Thuluva

•   Betreuer Rafael Peñaloza Nyssen
•   Automatentheorie
•   01. Oktober 2014 – 09. März 2015
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Ontologies, which form the core of Semantic Web systems, need to evolve to meet the changing needs of the system and its users. The dynamic nature of ontology development has motivated the formal study of ontology evolution problems, which is one of the important problems in the current Semantic Web research. Ontology evolution approaches suffer from intrinsic information loss. The current study deals with the problem of minimizing information loss during iterative ontology update. It provides a framework combining the ontology evolution tasks with context-based reasoning method. Using this framework, all the solutions obtained in an ontology evolution task, which are partly redundant, can be described as contexts and compactly represented in a single labelled ontology. Further updates and reasoning can be done on this ontology efficiently.

We propose new approaches to do ontology contraction, ontology expansion and ontology revision using context-based reasoning method. These approaches show how ontology evolution can be done with minimum information loss by using all the solutions obtained at every stage of the evolution task, efficiently using our framework. We also propose theoretical methods to extract the optimal solutions from the ontology obtained as the result of iterative ontology update. We show that, optimal solutions in the intermediate stages of iterative ontology update may not be the optimal solutions in the result obtained at the end of all the stages. We handle various notions of an optimal solution: the solution which changes the semantics of the ontology as minimum as possible, the solution which contains some of the intended consequences, the solution which has the most original axioms of the ontology. We also propose theoretical methods to do context-based reasoning over the optimal solutions extracted.

We present the first prototypical implementation of the theoretical methods developed in this thesis and show the preliminary results of our implementation on the real-world ontologies.