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Contribution Details
Type | Conference or Workshop Paper |
Scope | Discipline-based scholarship |
Published in Proceedings | Yes |
Title | On the evolution of ontologies using probabilistic description logics |
Organization Unit | |
Authors |
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Presentation Type | paper |
Item Subtype | Original Work |
Refereed | Yes |
Status | Published in final form |
Language |
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Event Title | First ESWC Workshop on Inductive Reasoning and Machine Learning on the Semantic Web |
Event Type | workshop |
Event Location | Heraklion, Greece |
Event Start Date | June 1 - 2009 |
Event End Date | June 1 - 2009 |
Abstract Text | Exceptions play an important role in conceptualizing data, especially when new knowledge is introduced or existing knowledge changes. Furthermore, real-world data often is contradictory and uncertain. Current formalisms for conceptualizing data like Description Logics rely upon first-order logic. As a consequence, they are poor in addressing exceptional, inconsistent and uncertain data, in particular when evolving the knowledge base over time. This paper investigates the use of Probabilistic Description Logics as a formalism for the evolution of ontologies that conceptualize real-world data. Different scenarios are presented for the automatic handling of inconsistencies during ontology evolution. |
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