Semantic Network Analysis of Ontologies
Semantic Network Analysis of Ontologies
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DOI：
10.1007/11762256_38
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发表时间：
2006-06
期刊：
影响因子：
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通讯作者：
Bettina Hoser;A. Hotho;R. Jäschke;Christoph Schmitz;Gerd Stumme
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文献类型：
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作者：
Bettina Hoser;A. Hotho;R. Jäschke;Christoph Schmitz;Gerd Stumme
在本体中建模知识的一个关键论点是知识的易于重用和重新设计。然而，目前的本体工程工具只提供基本的功能，分析本体。由于本体可以被认为是图，图分析技术是一个合适的答案，这需要。社会网络分析（Social Network Analysis，SNA）是社会学家在60多年前提出的一个生动的研究领域。虽然社会网络结构目前在语义Web社区受到高度关注，但SNA的应用很少，几乎没有用于分析本体结构的应用。我们说明了将SNA应用于本体和语义Web的好处，并讨论在这两个领域的边缘出现了哪些研究课题。特别是，我们讨论了如何不同的概念的中心描述的核心内容和结构的本体。从相对简单的介数中心度中心性概念到更复杂的特征向量中心性，我们说明了这些措施提供的两个本体论，这是不同的目的，范围和大小的见解。
A key argument for modeling knowledge in ontologies is the easy reuse and re-engineering of the knowledge. However, current ontology engineering tools provide only basic functionalities for analyzing ontologies. Since ontologies can be considered as graphs, graph analysis techniques are a suitable answer for this need. Graph analysis has been performed by sociologists for over 60 years, and resulted in the vivid research area of Social Network Analysis (SNA).While social network structures currently receive high attention in the Semantic Web community, there are only very few SNA applications, and virtually none for analyzing the structure of ontologies.We illustrate the benefits of applying SNA to ontologies and the Semantic Web, and discuss which research topics arise on the edge between the two areas. In particular, we discuss how different notions of centrality describe the core content and structure of an ontology. From the rather simple notion of degree centrality over betweenness centrality to the more complex eigenvector centrality, we illustrate the insights these measures provide on two ontologies, which are different in purpose, scope, and size.