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Approximating Model-Based ABox Revision in DL-Lite: Theory and Practice

机译:在DL-Lite中逼近模型的ABOX修订:理论与实践

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Model-based approaches provide a semantically well justified way to revise ontologies. However, in general, model-based revision operators are limited due to lack of efficient algorithms and inexpressibility of the revision results. In this paper, we make both theoretical and practical contribution to efficient computation of model-based revisions in DL-Lite. Specifically, we show that maximal approximations of two well-known model-based revisions for DL-Lite_R can be computed using a syntactic algorithm. However, such a coincidence of model-based and syntactic approaches does not hold when role functionality axioms are allowed. As a result, we identify conditions that guarantee such a coincidence for DL-Lite_(FR). Our result shows that both model-based and syntactic revisions can co-exist seamlessly and the advantages of both approaches can be taken in one revision operator. Based on our theoretical results, we develop a graph-based algorithm for the revision operators and thus graph database techniques can be used to compute ontology revisions. Preliminary evaluation results show that the graph-based algorithm can efficiently handle revision of practical ontologies with large data.
机译:基于模型的方法提供了一种修改本体的语义良好的理由方式。然而,通常,由于缺乏有效的算法和修订结果的无法形容,基于模型的修订算子受到限制。在本文中,我们对DL-Lite中基于模型的修订的有效计算进行了理论和实践贡献。具体地,我们示出了可以使用句法算法计算用于DL-Lite_R的两个基于模型的两个众所周知的基于模型的修订的最大近似。然而,在允许角色功能公理的情况下,这种基于模型和句法方法的这种重合不会保持。结果,我们确定了保证DL-Lite_(FR)这种巧合的条件。我们的结果表明,基于模型和句法修订都可以无缝地共存,并且可以在一个修订操作员中采取两种方法的优点。根据我们的理论结果,我们开发了一种基于图形的修订算法算法,因此图表数据库技术可用于计算本体修订。初步评估结果表明,基于图形的算法可以有效地处理具有大数据的实际本体的修订。

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