Reasoning with Probabilistic Ontologies
Abstract
Modeling real world domains requires ever more frequently to represent uncertain information. The DISPONTE semantics for probabilistic description logics allows to annotate axioms of a knowledge base with a value that represents their probability. In this paper we discuss approaches for performing inference from probabilistic ontologies following the DISPONTE semantics. We present the algorithm BUNDLE for computing the probability of queries. BUNDLE exploits an underlying Description Logic reasoner, such as Pellet, in order to find explanations for a query. These are then encoded in a Binary Decision Diagram that is used for computing the probability of the query.
Cite
Text
Riguzzi et al. "Reasoning with Probabilistic Ontologies." International Joint Conference on Artificial Intelligence, 2015.Markdown
[Riguzzi et al. "Reasoning with Probabilistic Ontologies." International Joint Conference on Artificial Intelligence, 2015.](https://mlanthology.org/ijcai/2015/riguzzi2015ijcai-reasoning/)BibTeX
@inproceedings{riguzzi2015ijcai-reasoning,
title = {{Reasoning with Probabilistic Ontologies}},
author = {Riguzzi, Fabrizio and Bellodi, Elena and Lamma, Evelina and Zese, Riccardo},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2015},
pages = {4310-4316},
url = {https://mlanthology.org/ijcai/2015/riguzzi2015ijcai-reasoning/}
}