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Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-25863

Scharrenbach, T; Bernstein, A (2009). On the evolution of ontologies using probabilistic description logics. In: First ESWC Workshop on Inductive Reasoning and Machine Learning on the Semantic Web, Heraklion, Greece, June 2009 - June 2009.

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Abstract

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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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Event End Date:June 2009
Deposited On:04 Feb 2010 11:27
Last Modified:09 Jul 2012 04:04

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