Learning General Concept Inclusions in Probabilistic Description Logics
Publikation: Beitrag zu Konferenzen › Paper › Beigetragen › Begutachtung
Beitragende
Abstract
Probabilistic interpretations consist of a set of interpretations with a shared domain and a measure assigning a probability to each interpretation. Such structures can be obtained as results of repeated experiments, e.g., in biology, psychology, medicine, etc. A translation between probabilistic and crisp description logics is introduced and then utilised to reduce the construction of a base of general concept inclusions of a probabilistic interpretation to the crisp case for which a method for the axiomatisation of a base of GCIs is well-known.
Details
Originalsprache | Englisch |
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Publikationsstatus | Veröffentlicht - 21 Sept. 2015 |
Peer-Review-Status | Ja |
Externe IDs
ORCID | /0000-0003-0219-0330/work/153109410 |
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