Name
Abstract | ||
|---|---|---|
On the one hand, classical terminological knowledge representation excludes the possibility of handling uncertain concept descriptions involving, e.g., "usually true" concept properties, generalized quantifiers, or exceptions. On the other hand, purely numerical approaches for handling uncertainty in general axe unable to consider terminological knowledge. This paper presents the language ACCP which is a probabilistic extension of terminological logics and aims at closing the gap between the two areas of research. We present the formal semantics underlying the language ACCP and introduce the probabilistic formalism that is based on classes of probabilities and is realized by means of probabilistic constraints. Besides infering implicitly existent probabilistic relationships, the constraints guarantee terminological and probabilistic consistency. Altogether, the new language ACCP applies to domains where both term descriptions and uncertainty have to be handled. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/B978-1-55860-332-5.50044-4 | UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence |
Keywords | Field | DocType |
terminological logic,existent probabilistic relationship,probabilistic constraint,probabilistic description logic,terminological knowledge,classical terminological knowledge representation,probabilistic formalism,probabilistic extension,new language,probabilistic consistency,language accp,description logic | Knowledge representation and reasoning,Usually true,Computer science,Description logic,Natural language processing,Artificial intelligence,Constructed language,Probabilistic logic,Formalism (philosophy),Semantics of logic | Journal |
Volume | ISBN | Citations |
abs/1302.6817 | 1-55860-332-8 | 59 |
PageRank | References | Authors |
3.96 | 15 | 1 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jochen Heinsohn | 1 | 145 | 41.56 |