Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
A probabilistic terminological logic for modelling information retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Machine Learning - Special issue on learning with probabilistic representations
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Introduction to Algorithms
ECML '93 Proceedings of the European Conference on Machine Learning
An algorithm based on counterfactuals for concept learning in the Semantic Web
Applied Intelligence
Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
Integrating Naïve Bayes and FOIL
The Journal of Machine Learning Research
Expressive probabilistic description logics
Artificial Intelligence
Hybrid Learning of Ontology Classes
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
DL-FOIL Concept Learning in Description Logics
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Loopy Propagation in a Probabilistic Description Logic
SUM '08 Proceedings of the 2nd international conference on Scalable Uncertainty Management
Tractable Reasoning with Bayesian Description Logics
SUM '08 Proceedings of the 2nd international conference on Scalable Uncertainty Management
PR-OWL: A Framework for Probabilistic Ontologies
Proceedings of the 2006 conference on Formal Ontology in Information Systems: Proceedings of the Fourth International Conference (FOIS 2006)
DBpedia - A crystallization point for the Web of Data
Web Semantics: Science, Services and Agents on the World Wide Web
A refinement operator based learning algorithm for the ALC description logic
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
Foundations of refinement operators for description logics
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Learning terminologies in probabilistic description logics
SBIA'10 Proceedings of the 20th Brazilian conference on Advances in artificial intelligence
Probabilistic description logics
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
A bisimulation-based method of concept learning for knowledge bases in description logics
Proceedings of the Third Symposium on Information and Communication Technology
Parameter learning for probabilistic ontologies
RR'13 Proceedings of the 7th international conference on Web Reasoning and Rule Systems
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Description logics have become a prominent paradigm in knowledge representation (particularly for the Semantic Web), but they typically do not include explicit representation of uncertainty. In this paper, we propose a framework for automatically learning a Probabilistic Description Logic from data. We argue that one must learn both concept definitions and probabilistic assignments. We also propose algorithms that do so and evaluate these algorithms on real data.