@inproceedings{hotho2006trend, title = {Trend Detection in Folksonomies}, address = {Heidelberg}, author = {Andreas Hotho and Robert Jäschke and Christoph Schmitz and Gerd Stumme}, booktitle = {Proc. First International Conference on Semantics And Digital Media Technology (SAMT) }, editor = {Yannis S. Avrithis and Yiannis Kompatsiaris and Steffen Staab and Noel E. O'Connor}, month = {dec}, pages = {56-70}, publisher = {Springer}, series = {LNCS}, volume = 4306, year = 2006, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006trend.pdf}, ee = {http://dx.doi.org/10.1007/11930334_5}, isbn = {3-540-49335-2}, vgwort = {27}, date = {2006-12-13}, abstract = {As the number of resources on the web exceeds by far the number of documents one can track, it becomes increasingly difficult to remain up to date on ones own areas of interest. The problem becomes more severe with the increasing fraction of multimedia data, from which it is difficult to extract some conceptual description of their contents. One way to overcome this problem are social bookmark tools, which are rapidly emerging on the web. In such systems, users are setting up lightweight conceptual structures called folksonomies, and overcome thus the knowledge acquisition bottleneck. As more and more people participate in the effort, the use of a common vocabulary becomes more and more stable. We present an approach for discovering topic-specific trends within folksonomies. It is based on a differential adaptation of the PageRank algorithm to the triadic hypergraph structure of a folksonomy. The approach allows for any kind of data, as it does not rely on the internal structure of the documents. In particular, this allows to consider different data types in the same analysis step. We run experiments on a large-scale real-world snapshot of a social bookmarking system.}, biburl = {http://www.bibsonomy.org/bibtex/242cda5911e901eadd0ac6a106a6aa1dc/jaeschke}, keywords = {2006 detection folksonomy l3s myown trend} } @inproceedings{jaeschke2006trias, title = {TRIAS - An Algorithm for Mining Iceberg Tri-Lattices}, address = {Hong Kong}, author = {Robert Jäschke and Andreas Hotho and Christoph Schmitz and Bernhard Ganter and Gerd Stumme}, booktitle = {Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 06)}, month = {December}, pages = {907-911}, publisher = {IEEE Computer Society}, year = 2006, url = {http://www.kde.cs.uni-kassel.de/jaeschke/paper/jaeschke06trias.pdf}, issn = {1550-4786}, isbn = {0-7695-2701-9}, vgwort = {19}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2006.162}, biburl = {http://www.bibsonomy.org/bibtex/2e387c294129e11f4221514d5fa807e26/jaeschke}, keywords = {12 2006 algorithm fca iccs_example l3s myown trias trias_example} } @inproceedings{hjss06bibsonomy, title = {{BibSonomy}: A Social Bookmark and Publication Sharing System}, address = {Aalborg, Denmark}, author = {Andreas Hotho and Robert Jäschke and Christoph Schmitz and Gerd Stumme}, booktitle = {Proceedings of the Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures}, editor = {Aldo de Moor and Simon Polovina and Harry Delugach}, month = {July}, publisher = {Aalborg University Press}, year = 2006, url = {http://www.kde.cs.uni-kassel.de/jaeschke/paper/hotho06bibsonomy.pdf}, isbn = {87-7307-769-0}, vgwort = {27}, biburl = {http://www.bibsonomy.org/bibtex/22cbd8e3236adea7c54779605a5aa4fd6/jaeschke}, keywords = {2006 bibsonomy bookmarking folksonomy iccs iccs_example l3s myown social trias_example} } @inproceedings{schmitz2006mining, title = {Mining Association Rules in Folksonomies}, address = {Berlin, Heidelberg}, annote = {Proc. of the 10th IFCS Conf.}, author = {Christoph Schmitz and Andreas Hotho and Robert Jäschke and Gerd Stumme}, booktitle = {Data Science and Classification}, editor = {V. Batagelj and H.-H. Bock and A. Ferligoj and A. Žiberna}, pages = {261--270}, publisher = {Springer}, series = {Studies in Classification, Data Analysis, and Knowledge Organization}, year = 2006, isbn = {978-3-540-34415-5}, biburl = {http://www.bibsonomy.org/bibtex/27f502f47bd0e584190337e3e2d4eba9e/jaeschke}, keywords = {2006 association folksonomy iccs_example l3s mining myown rule trias_example} } @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.}, biburl = {http://www.bibsonomy.org/bibtex/29a2c77c7c7a1b19cd16df08cca65f706/jaeschke}, keywords = {2006 analysis iccs_example l3s myown network ontology semantic trias_example} } @inproceedings{hotho2006emergent, title = {Emergent Semantics in BibSonomy}, address = {Bonn}, author = {Andreas Hotho and Robert Jäschke and Christoph Schmitz and Gerd Stumme}, booktitle = {Informatik 2006 - Informatik für Menschen. Band 2}, editor = {Christian Hochberger and Rüdiger Liskowsky}, month = {oct}, note = {Proc. Workshop on Applications of Semantic Technologies, Informatik 2006}, series = {Lecture Notes in Informatics}, volume = {P-94}, year = 2006, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006emergent.pdf}, issn = {1617-5468}, isbn = {978-3-88579-188-1}, vgwort = {14}, 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, briefly describe our own system BibSonomy, which allows for sharing both bookmarks and publication references, and discuss first steps towards emergent semantics.}, biburl = {http://www.bibsonomy.org/bibtex/205043cc20f1e0f5a612135c970e4f1ac/jaeschke}, keywords = {2006 bibsonomy emergent folksonomy iccs_example l3s myown semantic trias_example} } @inbook{schmitz2006kollaboratives, title = {Kollaboratives Wissensmanagement}, author = {Christoph Schmitz and Andreas Hotho and Robert Jäschke and Gerd Stumme}, booktitle = {Semantic Web - Wege zur vernetzten Wissensgesellschaft}, editor = {Tassilo Pellegrini and Andreas Blumauer}, pages = {273-290}, publisher = {Springer}, year = 2006, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006kollaboratives.pdf}, isbn = {3-540-29324-8}, abstract = {Wissensmanagement in zentralisierten Wissensbasen erfordert einen hohen Aufwand für Erstellung und Wartung, und es entspricht nicht immer den Anforderungen der Benutzer. Wir geben in diesem Kapitel einen Überblick über zwei aktuelle Ansätze, die durch kollaboratives Wissensmanagement diese Probleme lösen können. Im Peer-to-Peer-Wissensmanagement unterhalten Benutzer dezentrale Wissensbasen, die dann vernetzt werden können, um andere Benutzer eigene Inhalte nutzen zu lassen. Folksonomies versprechen, die Wissensakquisition so einfach wie möglich zu gestalten und so viele Benutzer in den Aufbau und die Pflege einer gemeinsamen Wissensbasis einzubeziehen.}, biburl = {http://www.bibsonomy.org/bibtex/253e13744981f2c04d9239e0cf9b4e689/jaeschke}, keywords = {2006 collaborative iccs_example knowledge l3s management myown semantic trias_example web} } @inproceedings{jaeschke06wege, title = {Wege zur Entdeckung von Communities in Folksonomies}, address = {Halle-Wittenberg}, author = {Robert Jäschke and Andreas Hotho and Christoph Schmitz and Gerd Stumme}, booktitle = {Proc. 18. Workshop Grundlagen von Datenbanken}, editor = {Stefan Braß and Alexander Hinneburg}, month = {June}, pages = {80-84}, publisher = {Martin-Luther-Universität }, year = 2006, url = {http://www.kde.cs.uni-kassel.de/jaeschke/pub/jaeschke2006wege_gvd.pdf}, abstract = {Ein wichtiger Baustein des neu entdeckten World Wide Web -- des "Web 2.0" -- stellen Folksonomies dar. In diesen Systemen können Benutzer gemeinsam Ressourcen verwalten und mit Schlagwörtern versehen. Die dadurch entstehenden begrifflichen Strukturen stellen ein interessantes Forschungsfeld dar. Dieser Artikel untersucht Ansätze und Wege zur Entdeckung und Strukturierung von Nutzergruppen ("Communities") in Folksonomies.}, biburl = {http://www.bibsonomy.org/bibtex/22b6be3bd5daee7119973fcf69909956f/jaeschke}, keywords = {2006 community detection folksonomy iccs_example l3s myown trias_example} } @inproceedings{hotho2006information, title = {Information Retrieval in Folksonomies: Search and Ranking}, address = {Heidelberg}, author = {Andreas Hotho and Robert Jäschke and Christoph Schmitz and Gerd Stumme}, booktitle = {The Semantic Web: Research and Applications}, editor = {York Sure and John Domingue}, month = {June}, pages = {411-426}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, volume = 4011, year = 2006, 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. At the moment, however, 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.}, biburl = {http://www.bibsonomy.org/bibtex/23c301945817681d637ee43901c016939/jaeschke}, keywords = {2006 folkrank folksonomy graph iccs_example information l3s mining myown pagerank rank ranking retrieval search seminar2006 trias_example} } @inproceedings{schmitz2006content, title = {Content Aggregation on Knowledge Bases using Graph Clustering}, address = {Budva, Montenegro}, author = {Christoph Schmitz and Andreas Hotho and Robert Jäschke and Gerd Stumme}, booktitle = {Proceedings of the 3rd European Semantic Web Conference}, month = {June}, year = 2006, abstract = {Recently, research projects such as PADLR and SWAP have developed tools like Edutella or Bibster, which are targeted at establishing peer-to-peer knowledge management (P2PKM) systems. In such a system, it is necessary to obtain provide brief semantic descriptions of peers, so that routing algorithms or matchmaking processes can make decisions about which communities peers should belong to, or to which peers a given query should be forwarded. This paper provides a graph clustering technique on knowledge bases for that purpose. Using this clustering, we can show that our strategy requires up to 58% fewer queries than the baselines to yield full recall in a bibliographic P2PKM scenario.}, biburl = {http://www.bibsonomy.org/bibtex/27d738e62dffd04f709e66de94c6dee89/jaeschke}, keywords = {2006 aggregation clustering graph iccs_example knowledge l3s myown trias_example} }