@inproceedings{hoser2006semantic, abstract = {A key argument for modeling knowledge in ontologies is the easy re-use and re-engineering of the knowledge. However, beside consistency checking, current ontology engineering tools provide only basic functionalities for analyzing ontologies. Since ontologies can be considered as (labeled, directed) 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 in general currently receive high attention in the Semantic Web community, there are only very few SNA applications up to now, and virtually none for analyzing the structure of ontologies. We illustrate in this paper 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 based on Hermitian matrices, we illustrate the insights these measures provide on two ontologies, which are different in purpose, scope, and size.}, address = {Heidelberg}, author = {Hoser, Bettina and Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd}, booktitle = {The Semantic Web: Research and Applications}, editor = {Sure, York and Domingue, John}, interhash = {344ec3b4ee8af1a2c6b86efc14917fa9}, intrahash = {c0cdbeab23ce0fc1bff5e02c99aab012}, month = {June}, pages = {514-529}, publisher = {Springer}, series = {LNAI}, title = {Semantic Network Analysis of Ontologies}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hoser2006semantic.pdf}, volume = 4011, year = 2006 } @proceedings{alani2006proceedings, editor = {Alani, Harith and Hoser, Bettina and Schmitz, Christoph and Stumme, Gerd}, interhash = {e991143409a8f4acb9eabfe08a38e387}, intrahash = {786a452a14c5189d82dc56f16cc2a266}, title = {Proceedings of the 2nd Workshop on Semantic Network Analysis}, url = {http://www.kde.cs.uni-kassel.de/ws/sna2006/}, year = 2006 } @inproceedings{hotho2006bibsonomy, abstract = {Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. In this paper we specify a formal model for folksonomies and briefly describe our own system BibSonomy, which allows for sharing both bookmarks and publication references in a kind of personal library.}, address = {Aalborg}, author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd}, booktitle = {Proceedings of the First Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures}, editor = {de Moor, Aldo and Polovina, Simon and Delugach, Harry}, interhash = {d28c9f535d0f24eadb9d342168836199}, intrahash = {5854a71547051543dd3d3d5e2e2f2b67}, isbn = {87-7307-769-0}, pages = {87-102}, publisher = {Aalborg Universitetsforlag}, title = {{BibSonomy}: A Social Bookmark and Publication Sharing System}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006bibsonomy.pdf}, year = 2006 } @inproceedings{schmitz2006mining, abstract = {Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. These systems provide currently relatively few structure. We discuss in this paper, how association rule mining can be adopted to analyze and structure folksonomies, and how the results can be used for ontology learning and supporting emergent semantics. We demonstrate our approach on a large scale dataset stemming from an online system.}, address = {Heidelberg}, author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd}, booktitle = {Data Science and Classification. Proceedings of the 10th IFCS Conf.}, editor = {Batagelj, V. and Bock, H.-H. and Ferligoj, A. and Žiberna, A.}, interhash = {20650d852ca3b82523fcd8b63e7c12d7}, intrahash = {11b2a59a568d246d7f36cb68169a464a}, month = {July}, pages = {261--270}, publisher = {Springer}, series = {Studies in Classification, Data Analysis, and Knowledge Organization}, title = {Mining Association Rules in Folksonomies}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/schmitz2006mining.pdf}, year = 2006 } @inproceedings{hotho2006folkrank, abstract = { In social bookmark tools users are setting up lightweight conceptual structures called folksonomies. Currently, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset. A long version of this paper has been published at the European Semantic Web Conference 2006.}, author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd}, booktitle = {Proc. FGIR 2006}, interhash = {3468dc3fed17eadf2e7c6ff06fbb34a3}, intrahash = {4d8b4f79814691fbe6db8357d63206a1}, title = {FolkRank: A Ranking Algorithm for Folksonomies}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006folkrank.pdf}, year = 2006 }