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Probabilistic Query Answering in the Bayesian Description Logic BEL

机译:贝叶斯描述逻辑BEL中的概率查询应答

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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.
机译:BEL是一种概率描述逻辑(DL),它通过公理在贝叶斯网络(BN)的帮助下以公理上的联合概率分布扩展了轻量级DL EL。在最近的工作中,已经表明BEL中标准逻辑推理的复杂性与对BN进行概率推理相同。在本文中,我们考虑了BEL中的联合查询应答。我们研究了与此设置相关的三个主要问题的复杂性:计算查询涉及的概率,计算查询的最可能答案以及计算查询所涉及的最可能的上下文。特别是,我们证明所有这些问题都是可以解决的。数据和本体的复杂性。

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