Abstract. One shortcoming of classic Descriptions Logics, DLs, is their inability to encode probabilistic knowledge and reason over it. This is, however, a strong demand of some modern applications, e.g. in biology and healthcare. Therefore, probabilistic extensions of DLs are attracting attention nowadays. We introduce the probabilistic DL SHIQP which extends a known probabilistic DL. We investigate two reasoning problems for TBoxes: deciding consistency and computing tight probability bounds. It turns out that both problems are not harder than reasoning in the classic counterpart SHIQ. We gain insight into complexity sources
Abstract. Representing uncertain information is crucial for modeling real world domains. In this pap...
Representing uncertain information is crucial for modeling real world domains. In this paper we pres...
Representing uncertain information is crucial for modeling real world domains. In this paper we pres...
Abstract. One shortcoming of classic Descriptions Logics, DLs, is their inability to encode probabil...
We propose a family of probabilistic description logics (DLs) that are derived in a principled way f...
AbstractThe work in this paper is directed towards sophisticated formalisms for reasoning under prob...
The work in this paper is directed towards sophisticated formalisms for reasoning under probabilisti...
Description logics (DLs) are well-known knowledge representation formalisms focused on the represent...
Ontologies play a central role in the development of the Semantic Web, as they provide precise defin...
Description logics in their standard setting only allow for representing and reasoning with crisp kn...
We propose a general scheme for adding probabilistic reasoning capabilities to any knowledge represe...
Ontologies play a central role in the development of the semantic web, as they provide precise defin...
We propose a general scheme for adding probabilistic reasoning capabilities to a wide variety of kno...
Probabilistic Description Logics (ProbDLs) are an extension of Description Logics that are designed ...
Description logics (DLs) are well-known knowledge representation formalisms focused on the represent...
Abstract. Representing uncertain information is crucial for modeling real world domains. In this pap...
Representing uncertain information is crucial for modeling real world domains. In this paper we pres...
Representing uncertain information is crucial for modeling real world domains. In this paper we pres...
Abstract. One shortcoming of classic Descriptions Logics, DLs, is their inability to encode probabil...
We propose a family of probabilistic description logics (DLs) that are derived in a principled way f...
AbstractThe work in this paper is directed towards sophisticated formalisms for reasoning under prob...
The work in this paper is directed towards sophisticated formalisms for reasoning under probabilisti...
Description logics (DLs) are well-known knowledge representation formalisms focused on the represent...
Ontologies play a central role in the development of the Semantic Web, as they provide precise defin...
Description logics in their standard setting only allow for representing and reasoning with crisp kn...
We propose a general scheme for adding probabilistic reasoning capabilities to any knowledge represe...
Ontologies play a central role in the development of the semantic web, as they provide precise defin...
We propose a general scheme for adding probabilistic reasoning capabilities to a wide variety of kno...
Probabilistic Description Logics (ProbDLs) are an extension of Description Logics that are designed ...
Description logics (DLs) are well-known knowledge representation formalisms focused on the represent...
Abstract. Representing uncertain information is crucial for modeling real world domains. In this pap...
Representing uncertain information is crucial for modeling real world domains. In this paper we pres...
Representing uncertain information is crucial for modeling real world domains. In this paper we pres...