Please use this identifier to cite or link to this item:
doi:10.22028/D291-24824
Title: | A hybrid approach for modeling uncertainty in terminological logics |
Author(s): | Heinsohn, Jochen |
Language: | English |
Year of Publication: | 1991 |
OPUS Source: | Kaiserslautern ; Saarbrücken : DFKI, 1991 |
SWD key words: | Künstliche Intelligenz Terminologische Sprache |
DDC notations: | 004 Computer science, internet |
Publikation type: | Report |
Abstract: | This paper proposes a probabilistic extension of terminological logics. The extension maintains the original performance of drawing inferences in a hierarchy of terminological definitions. It enlarges the range of applicability to real world domains determined not only by definitional but also by uncertain knowledge. First, we introduce the propositionally complete terminological language ALC. On the basis of the language construct "probabilistic implication" it is shown how statistical information on concept dependencies can be represented. To guarantee (terminological and probabilistic) consistency, several requirements have to be met. Moreover, these requirements allow one to infer implicitly existent probabilistic relationships and their quantitative computation. By explicitly introducing restrictions for the ranges derived by instantiating the consistency requirements, exceptions can also be handled. In the categorical cases this corresponds to the overriding of properties in non monotonic inheritance networks. Consequently, our model applies to domains where both term descriptions and non-categorical relations between term extensions have to be represented. |
Link to this record: | urn:nbn:de:bsz:291-scidok-35698 hdl:20.500.11880/24880 http://dx.doi.org/10.22028/D291-24824 |
Series name: | Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x] |
Series volume: | 91-24 |
Date of registration: | 16-May-2011 |
Faculty: | SE - Sonstige Einrichtungen |
Department: | SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz |
Collections: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
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RR_91_24.pdf | 11,97 MB | Adobe PDF | View/Open |
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