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|Abstract=Many formalisms combining ontology languages with uncertainty, usually in the form of probabilities, have been studied over the years. Most of these formalisms, however, assume that the probabilistic structure of the knowledge remains static over time. We present a general approach for extending ontology languages to handle time-evolving uncertainty represented by a dynamic Bayesian network. We show how reasoning in the original language and dynamic Bayesian inferences can be exploited for effective reasoning in our framework. | |Abstract=Many formalisms combining ontology languages with uncertainty, usually in the form of probabilities, have been studied over the years. Most of these formalisms, however, assume that the probabilistic structure of the knowledge remains static over time. We present a general approach for extending ontology languages to handle time-evolving uncertainty represented by a dynamic Bayesian network. We show how reasoning in the original language and dynamic Bayesian inferences can be exploited for effective reasoning in our framework. | ||
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|Forschungsgruppe=Automatentheorie | |Forschungsgruppe=Automatentheorie | ||
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Aktuelle Version vom 9. September 2015, 15:42 Uhr
Dynamic Bayesian Ontology Languages
İsmail İlkan Ceylanİsmail İlkan Ceylan, Rafael PeñalozaRafael Peñaloza
İsmail İlkan Ceylan, Rafael Peñaloza
Dynamic Bayesian Ontology Languages
Fifth International Workshop on Statistical Relational AI, volume abs/1506.08030, 2015. CoRR
Dynamic Bayesian Ontology Languages
Fifth International Workshop on Statistical Relational AI, volume abs/1506.08030, 2015. CoRR
- KurzfassungAbstract
Many formalisms combining ontology languages with uncertainty, usually in the form of probabilities, have been studied over the years. Most of these formalisms, however, assume that the probabilistic structure of the knowledge remains static over time. We present a general approach for extending ontology languages to handle time-evolving uncertainty represented by a dynamic Bayesian network. We show how reasoning in the original language and dynamic Bayesian inferences can be exploited for effective reasoning in our framework. - Forschungsgruppe:Research Group: AutomatentheorieAutomata Theory
@inproceedings{CP2015,
author = {{\.{I}}smail {\.{I}}lkan Ceylan and Rafael Pe{\~{n}}aloza},
title = {Dynamic Bayesian Ontology Languages},
booktitle = {Fifth International Workshop on Statistical Relational {AI}},
volume = {abs/1506.08030},
publisher = {CoRR},
year = {2015}
}
