Debugging and repair of description logic ontologies.
Debugging and repair of description logic ontologies.
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发表时间：
2010
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通讯作者：
Kodylan Moodley
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作者：
Kodylan Moodley
在基于逻辑的知识表示和推理（KRR）中，本体用于以精确的方式表示关于特定感兴趣领域的知识。本体的构建块包括概念、关系和对象。这些可以组合成明确描述域的逻辑句子。有了这些明确的知识，人们可以进行推理，以获得本体中隐含的知识。描述逻辑（DL）是一组知识表示语言，具有适合表示本体的能力。随着SWOOP、Protege和OntoStudio等图形化本体编辑器的出现，构建本体的过程已经大大简化。这样做的结果是，有越来越多的本体工程师试图建立和开发本体。在构建本体时引入错误，从而导致从本体得出的不期望的隐含知识片段，这是经常发生的情况。因此，有必要扩展当前的本体编辑器的工具支持，以帮助这些本体工程师正确地设计和调试他们的本体。在本体构建过程中，概念不满足、本体不一致等错误经常出现。本体修复和修复关注的是帮助本体开发者从本体中消除这些错误。在当前的工具中，很多重点都放在解释本体中为什么会出现这些错误上。较少强调使用这些信息来建议消除错误的有效方法。此外，这些工具主要集中在不可满足的概念和不一致的本体的错误。在这篇论文中，我们填补了一个重要的空白，在该地区的贡献本体调试和修复更一般的错误列表不需要的句子的替代方法。诸如不可满足的概念和不一致的本体之类的错误可以被表示为本体中不需要的句子。我们的方法不仅考虑不需要的句子的解释，但也确定修复策略，以消除这些不需要的句子从本体。
In logic-based Knowledge Representation and Reasoning (KRR), ontologies are used to represent knowledge about a particular domain of interest in a precise way. The building blocks of ontologies include concepts, relations and objects. Those can be combined to form logical sentences which explicitly describe the domain. With this explicit knowledge one can perform reasoning to derive knowledge that is implicit in the ontology. Description Logics (DLs) are a group of knowledge representation languages with such capabilities that are suitable to represent ontologies. The process of building ontologies has been greatly simplified with the advent of graphical ontology editors such as SWOOP, Protege and OntoStudio. The result of this is that there are a growing number of ontology engineers attempting to build and develop ontologies. It is frequently the case that errors are introduced while constructing the ontology resulting in undesirable pieces of implicit knowledge that follows from the ontology. As such there is a need to extend current ontology editors with tool support to aid these ontology engineers in correctly designing and debugging their ontologies. Errors such as unsatisfiable concepts and inconsistent ontologies frequently occur during ontology construction. Ontology Debugging and Repair is concerned with helping the ontology developer to eliminate these errors from the ontology. Much emphasis, in current tools, has been placed on giving explanations as to why these errors occur in the ontology. Less emphasis has been placed on using this information to suggest efficient ways to eliminate the errors. Furthermore, these tools focus mainly on the errors of unsatisfiable concepts and inconsistent ontologies. In this dissertation we fill an important gap in the area by contributing an alternative approach to ontology debugging and repair for the more general error of a list of unwanted sentences. Errors such as unsatisfiable concepts and inconsistent ontologies can be represented as unwanted sentences in the ontology. Our approach not only considers the explanation of the unwanted sentences but also the identification of repair strategies to eliminate these unwanted sentences from the ontology.