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Semantic Network Analysis of Ontologies

  • A key argument for modeling knowledge in ontologies is the easy re-use 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.

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Metadaten
Author:Bettina Hoser, Andreas Hotho, Robert Jäschke, Christoph Schmitz, Gerd Stumme
URN:https://nbn-resolving.org/urn:nbn:de:gbv:hil2-opus-389
Document Type:Conference Proceeding
Language:English
Date of Publication (online):2011/04/21
Contributing Corporation:Chair of Informationservices and Electronic Markets, Universitaet Karlsruhe
Release Date:2011/04/21
Source:KDML 2006: Knowledge Discovery, Data Mining, and Machine Learning 9.-13. Oktober 2006, Hildesheim
PPN:Link zum Katalog
Contributor:Althoff, Klaus-Dieter
Institutes:Fachbereich IV / Informatik
DDC classes:000 Allgemeines, Informatik, Informationswissenschaft / 000 Allgemeines, Wissenschaft / 004 Informatik
Licence (German):License LogoDeutsches Urheberrecht