While there exist several reasoners for Description Logics, very few of them can cope with uncertainty. BUNDLE is an inference framework that can exploit several OWL (non-probabilistic) reasoners to perform inference over Probabilistic Description Logics. In this chapter, we report the latest advances implemented in BUNDLE. In particular, BUNDLE can now interface with the reasoners of the TRILL system, thus providing a uniform method to execute probabilistic queries using different settings. BUNDLE can be easily extended and can be used either as a standalone desktop application or as a library in OWL API-based applications that need to reason over Probabilistic Description Logics. The reasoning performance heavily depends on the reasoner...
Modeling real world domains requires ever more frequently to represent uncertain information. The ...
AbstractTowards sophisticated representation and reasoning techniques that allow for probabilistic u...
Towards uncertainty reasoning in the Rules, Logic, and Proof layers of the Semantic Web, we present ...
While many systems exist for reasoning with Description Logics knowledge bases, very few of them are...
We present the web application TRILL on SWISH, which allows the user to write probabilistic Descript...
The increasing popularity of the Semantic Web drove to a widespread adoption of Description Logics (...
We present a semantics for Probabilistic Description Logics that is based on the distribution semant...
The adoption of Description Logics for modeling real world domains within the Semantic Web is expone...
The work in this paper is directed towards sophisticated formalisms for reasoning under probabilisti...
The increasing popularity of the Semantic Web drove to a widespread adoption of Description Logics (...
AbstractThe work in this paper is directed towards sophisticated formalisms for reasoning under prob...
One of the foremost reasoning services for knowledge bases is finding all the justifications for a q...
When modeling real-world domains, we have to deal with information that is incomplete or that comes ...
Finding explanations for queries to Description Logics (DL) theories is a non-standard reasoning se...
Representing uncertain information is crucial for modeling real world domains. This has been fully r...
Modeling real world domains requires ever more frequently to represent uncertain information. The ...
AbstractTowards sophisticated representation and reasoning techniques that allow for probabilistic u...
Towards uncertainty reasoning in the Rules, Logic, and Proof layers of the Semantic Web, we present ...
While many systems exist for reasoning with Description Logics knowledge bases, very few of them are...
We present the web application TRILL on SWISH, which allows the user to write probabilistic Descript...
The increasing popularity of the Semantic Web drove to a widespread adoption of Description Logics (...
We present a semantics for Probabilistic Description Logics that is based on the distribution semant...
The adoption of Description Logics for modeling real world domains within the Semantic Web is expone...
The work in this paper is directed towards sophisticated formalisms for reasoning under probabilisti...
The increasing popularity of the Semantic Web drove to a widespread adoption of Description Logics (...
AbstractThe work in this paper is directed towards sophisticated formalisms for reasoning under prob...
One of the foremost reasoning services for knowledge bases is finding all the justifications for a q...
When modeling real-world domains, we have to deal with information that is incomplete or that comes ...
Finding explanations for queries to Description Logics (DL) theories is a non-standard reasoning se...
Representing uncertain information is crucial for modeling real world domains. This has been fully r...
Modeling real world domains requires ever more frequently to represent uncertain information. The ...
AbstractTowards sophisticated representation and reasoning techniques that allow for probabilistic u...
Towards uncertainty reasoning in the Rules, Logic, and Proof layers of the Semantic Web, we present ...