Probabilistic Query Answering in the Bayesian Description Logic BEL

İsmail İlkan Ceylanİsmail İlkan Ceylan, Rafael PeñalozaRafael Peñaloza

Download

İsmail İlkan Ceylan, Rafael Peñaloza
Probabilistic Query Answering in the Bayesian Description Logic BEL
In Christoph Beierle, Alex Dekhtyar, eds., Proceedings of 9th International Conference on Scalable Uncertainty Management (SUM 2015), volume 9310 of LNAI, 1-15, 2015. Springer

Details
Bibtex

KurzfassungAbstract
BEL is a probabilistic description logic (DL) that extends the light-weight DL EL with a joint probability distribution over the axioms, expressed with the help of a Bayesian network (BN). In recent work it has been shown that the complexity of standard logical reasoning in BEL is the same as performing probabilistic inferences over the BN. In this paper we consider conjunctive query answering in BEL. We study the complexity of the three main problems associated to this setting: computing the probability of a query entailment, computing the most probable answers to a query, and computing the most probable context in which a query is entailed. In particular, we show that all these problems are tractable w.r.t. data and ontology complexity.
Forschungsgruppe:Research Group: AutomatentheorieAutomata Theory

The final publication is available at Springer.

@inproceedings{CP2015,
  author    = {{\.{I}}smail {\.{I}}lkan Ceylan and Rafael Pe{\~{n}}aloza},
  title     = {Probabilistic Query Answering in the Bayesian Description Logic
               {BEL}},
  editor    = {Christoph Beierle and Alex  Dekhtyar},
  booktitle = {Proceedings of 9th International Conference on Scalable
               Uncertainty Management (SUM 2015)},
  series    = {LNAI},
  volume    = {9310},
  publisher = {Springer},
  year      = {2015},
  pages     = {1-15}
}