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Axiomatisation of general concept inclusions from finite interpretations

机译:有限解释的一般概念包含物公理化

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摘要

Description logic knowledge bases can be used to represent knowledge about a particular domain in a formal and unambiguous manner. Their practical relevance has been shown in many research areas, especially in biology and the Semantic Web. However, the tasks of constructing knowledge bases itself, often performed by human experts, is difficult, time-consuming and expensive. In particular the synthesis of terminological knowledge is a challenge that every expert has to face. Because human experts cannot be omitted completely from the construction of knowledge bases, it would therefore be desirable to at least get some support from machines during this process. To this end, we shall investigate in this work an approach which shall allow us to extract terminological knowledge in the form of general concept inclusions from factual data, where the data is given in the form of vertex- and edge-labelled graphs. Because such graphs appear naturally within the scope of the Semantic Web in the form of sets of Resource Description Framework (RDF) triples, the presented approach opens up another possibility to extract terminological knowledge from the Linked Open Data Cloud.
机译:描述逻辑知识库可用于以形式明确的方式表示有关特定领域的知识。它们的实际相关性已在许多研究领域得到证明,尤其是在生物学和语义网中。但是,通常由人类专家执行的构建知识库本身的任务是困难,耗时且昂贵的。特别是,术语知识的综合是每个专家都必须面对的挑战。由于不能从知识库的构建中完全省略人类专家,因此希望在此过程中至少从机器中获得一些支持。为此,我们将在这项工作中研究一种方法,该方法应允许我们从事实数据中以一般概念包含的形式提取术语知识,其中,数据是以顶点和边标记图的形式给出的。因为这样的图以三组资源描述框架(RDF)的形式自然出现在语义网的范围内,所以本文提出的方法为从链接的开放数据云中提取术语知识开辟了另一种可能性。

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