Tractable approximate deduction for OWL
Tractable approximate deduction for OWL
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DOI：
10.1016/j.artint.2015.10.004
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发表时间：
2016-06-01
影响因子：
14.4
通讯作者：
Zhao, Yuting
中科院分区：
文献类型：
--
作者：
Pan, Jeff Z.;Ren, Yuan;Zhao, Yuting
今天的本体应用需要高效可靠的描述逻辑(DL)推理服务。表现性DLS通常具有较高的最坏情况复杂性，而易驯服的DLS在表达能力方面受到限制。这带来了一个新的挑战：用户能否使用富有表现力的DLS来构建他们的本体，并仍然像在易处理的语言中那样享受高效的服务？近似一直被认为是解决这一挑战的一种方法；然而，传统的近似方法在性能和可用性方面存在局限性。本文提出了一种易于处理的OWL2近似推理框架，提高了推理效率，并保证了推理的可靠性。基于基准测试和真实用例的本体测试表明，该方法能够高效地对复杂本体进行推理，并具有较高的召回率。(C)2016年，由爱思唯尔出版。
Today's ontology applications require efficient and reliable description logic (DL) reasoning services. Expressive DLs usually have high worst case complexity while tractable DLs are restricted in terms of expressive power. This brings a new challenge: can users use expressive DLs to build their ontologies and still enjoy the efficient services as in tractable languages? Approximation has been considered as a solution to this challenge; however, traditional approximation approaches have limitations in terms of performance and usability. In this paper, we present a tractable approximate reasoning framework for OWL 2 that improves efficiency and guarantees soundness. Evaluation on ontologies from benchmarks and real-world use cases shows that our approach can do reasoning on complex ontologies efficiently with a high recall. (C) 2016 Published by Elsevier B.V.