Tightly integrated probabilistic description logic programs for representing ontology mappings
Tightly integrated probabilistic description logic programs for representing ontology mappings
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DOI：
10.1007/s10472-012-9280-3
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发表时间：
2008-02
影响因子：
1.2
通讯作者：
Thomas Lukasiewicz;L. Predoiu;H. Stuckenschmidt
中科院分区：
文献类型：
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作者：
Thomas Lukasiewicz;L. Predoiu;H. Stuckenschmidt
在本体之间建立映射是解决语义Web上语义异构问题的一种常用方法。为了适应语义Web语言的景观，一个合适的，基于逻辑的表示形式主义的映射是必要的。我们认为，这样的形式主义必须能够处理自动创建的映射中的不确定性和不一致性。我们分析了这样的形式主义的要求，我们提出了一种新的方法，概率描述逻辑程序，这样的形式主义，紧密结合正常的逻辑程序下，有根据的语义与易于处理的本体语言和贝叶斯概率。我们定义的语言，我们表明，它可以用来解决不一致和合并映射从不同的匹配器的基础上分配给不同的规则的置信水平。此外，我们探讨了概率描述逻辑程序的语义和计算方面的良基语义。特别是，我们证明了良好的基础语义近似的答案集语义。我们还描述了算法的一致性检查和紧密的查询处理，我们分析了这两个中心的计算问题的数据和一般的复杂性。作为一个重要的属性，新的紧密集成的概率描述逻辑程序的良好的基础语义下，允许易处理的一致性检查和易处理的紧密查询处理的数据复杂性，他们甚至有一个一阶的数据（因此LogSpacedata复杂性）的特殊情况下，这是特别有趣的本体映射。
Creating mappings between ontologies is a common way of approaching the semantic heterogeneity problem on the Semantic Web. To fit into the landscape of Semantic Web languages, a suitable, logic-based representation formalism for mappings is needed. We argue that such a formalism has to be able to deal with uncertainty and inconsistencies in automatically created mappings. We analyze the requirements for such a formalism, and we propose a novel approach to probabilistic description logic programs as such a formalism, which tightly combines normal logic programs under the well-founded semantics with both tractable ontology languages and Bayesian probabilities. We define the language, and we show that it can be used to resolve inconsistencies and merge mappings from different matchers based on the level of confidence assigned to different rules. Furthermore, we explore the semantic and computational aspects of probabilistic description logic programs under the well-founded semantics. In particular, we show that the well-founded semantics approximates the answer set semantics. We also describe algorithms for consistency checking and tight query processing, and we analyze the data and general complexity of these two central computational problems. As a crucial property, the novel tightly integrated probabilistic description logic programs under the well-founded semantics allow for tractable consistency checking and for tractable tight query processing in the data complexity, and they even have a first-order rewritable (and thus LogSpacedata complexity) special case, which is especially interesting for representing ontology mappings.