| Authors: |
Bettina Hoser
and Andreas Hotho
and Robert Jäschke
and Christoph Schmitz
and Gerd Stumme
|
| Tags: |
2006
analysis
iccs_example
l3s
myown
network
ontology
semantic
trias_example
|
| Abstract: |
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. |
@inproceedings{hoser2006semantic,
title = {Semantic Network Analysis of Ontologies},
author = {Bettina Hoser and Andreas Hotho and Robert Jäschke and Christoph Schmitz and Gerd Stumme},
booktitle = {The Semantic Web: Research and Applications},
month = {June},
note = {Proceedings of the 3rd European Semantic Web Conference, Budva, Montenegro},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
year = {2006},
abstract = {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.},
keywords = {2006 analysis iccs_example l3s myown network ontology semantic trias_example }
}
::