Tag Recommendations in Folksonomies.
In: J. N. Kok, J. Koronacki, R. L. de Mántaras, S. Matwin, D. Mladenic and A. Skowron, editors,
Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, volume 4702, series Lecture Notes in Computer Science, pages 506-514.
Springer, Berlin, Heidelberg, 2007.
Robert Jäschke, Leandro Balby Marinho, Andreas Hotho, Lars Schmidt-Thieme and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
Collaborative tagging systems allow users to assign keywords—so called “tags”—to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied.
In this paper we evaluate and compare two recommendation algorithms on largescale real life datasets: an adaptation of user-based collaborative filtering and a graph-based recommender built on top of FolkRank. We show that both provide better results than non-personalized baseline methods. Especially the graph-based recommender outperforms existing methods considerably.
Proceedings of the 2nd Workshop on Semantic Network Analysis.
2006.
Harith Alani, Bettina Hoser, Christoph Schmitz and Gerd Stumme.
[doi]
[BibTeX]
Semantic Network Analysis of Ontologies.
In: Y. Sure and J. Domingue, editors,
The Semantic Web: Research and Applications, volume 4011, series LNAI, pages 514-529.
Springer, Heidelberg, 2006.
Bettina Hoser, Andreas Hotho, Robert Jäschke, Christoph Schmitz and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
BibSonomy: A Social Bookmark and Publication Sharing System.
In: A. de Moor, S. Polovina and H. Delugach, editors,
Proceedings of the First Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures, pages 87-102.
Aalborg Universitetsforlag, Aalborg, 2006.
Andreas Hotho, Robert Jäschke, Christoph Schmitz and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
Social bookmark tools are rapidly emerging on the Web. In suchsystems users are setting up lightweight conceptual structurescalled folksonomies. The reason for their immediate success is thefact that no specific skills are needed for participating. In thispaper we specify a formal model for folksonomies and briefly describe our own system BibSonomy, which allows for sharing both bookmarksand publication references in a kind of personal library.
BibSonomy: A Social Bookmark and Publication Sharing System.
In: A. de Moor, S. Polovina and H. Delugach, editors,
Proceedings of the First Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures, pages 87-102.
Aalborg Universitetsforlag, Aalborg, 2006.
Andreas Hotho, Robert Jäschke, Christoph Schmitz and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Das Entstehen von Semantik in BibSonomy.
In:
Social Software in der Wertschöpfung.
Nomos, Baden-Baden, 2006.
Andreas Hotho, Robert Jäschke, Christoph Schmitz and Gerd Stumme.
[doi] [pdf]
[abstract]
[BibTeX]
Immer mehr Soziale-Lesezeichen-Systeme entstehen im heutigen Web. In solchen Systemen erstellen die Nutzer leichtgewichtige begriffliche Strukturen, so genannte Folksonomies. Ihren Erfolg verdanken sie der Tatsache, dass man keine speziellen Fähigkeiten benötigt, um an der Gestaltung mitzuwirken. In diesem Artikel beschreiben wir unser System BibSonomy. Es erlaubt das Speichern, Verwalten und Austauschen sowohl von Lesezeichen (Bookmarks) als auch von Literaturreferenzen in Form von BibTeX-Einträgen. Die Entwicklung des verwendeten Vokabulars und der damit einhergehenden Entstehung einer gemeinsamen Semantik wird detailliert diskutiert.
Emergent Semantics in BibSonomy.
In: C. Hochberger and R. Liskowsky, editors,
Informatik 2006 - Informatik für Menschen. Band 2, volume P-94, series Lecture Notes in Informatics.
Gesellschaft für Informatik, Bonn, 2006.
Proc. Workshop on Applications of Semantic Technologies, Informatik 2006
Andreas Hotho, Robert Jäschke, Christoph Schmitz and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
Social bookmark tools are rapidly emerging on the Web. In suchsystems users are setting up lightweight conceptual structurescalled folksonomies. The reason for their immediate success is thefact that no specific skills are needed for participating. In thispaper we specify a formal model for folksonomies, briefly describeour own system BibSonomy, which allows for sharing both bookmarks andpublication references, and discuss first steps towards emergent semantics.
Emergent Semantics in BibSonomy.
In: C. Hochberger and R. Liskowsky, editors,
Informatik 2006 - Informatik für Menschen. Band 2, volume P-94, series Lecture Notes in Informatics.
Gesellschaft für Informatik, Bonn, 2006.
Proc. Workshop on Applications of Semantic Technologies, Informatik 2006
Andreas Hotho, Robert Jäschke, Christoph Schmitz and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
Social bookmark tools are rapidly emerging on the Web. In suchsystems users are setting up lightweight conceptual structurescalled folksonomies. The reason for their immediate success is thefact that no specific skills are needed for participating. In thispaper we specify a formal model for folksonomies, briefly describeour own system BibSonomy, which allows for sharing both bookmarks andpublication references, and discuss first steps towards emergent semantics.
FolkRank: A Ranking Algorithm for Folksonomies.
In:
Proc. FGIR 2006.
2006.
Andreas Hotho, Robert Jäschke, Christoph Schmitz and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Trend Detection in Folksonomies.
In: Y. S. Avrithis, Y. Kompatsiaris, S. Staab and N. E. O'Connor, editors,
Proc. First International Conference on Semantics And Digital Media Technology (SAMT) , volume 4306, series LNCS, pages 56-70.
Springer, Heidelberg, 2006.
Andreas Hotho, Robert Jäschke, Christoph Schmitz and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
As the number of resources on the web exceeds by far the number ofdocuments one can track, it becomes increasingly difficult to remainup to date on ones own areas of interest. The problem becomes moresevere with the increasing fraction of multimedia data, from whichit is difficult to extract some conceptual description of theircontents.One way to overcome this problem are social bookmark tools, whichare rapidly emerging on the web. In such systems, users are settingup lightweight conceptual structures called folksonomies, andovercome thus the knowledge acquisition bottleneck. As more and morepeople participate in the effort, the use of a common vocabularybecomes more and more stable. We present an approach for discoveringtopic-specific trends within folksonomies. It is based on adifferential adaptation of the PageRank algorithm to the triadichypergraph structure of a folksonomy. The approach allows for anykind of data, as it does not rely on the internal structure of thedocuments. In particular, this allows to consider different datatypes in the same analysis step. We run experiments on a large-scalereal-world snapshot of a social bookmarking system.
Trend Detection in Folksonomies.
In: Y. S. Avrithis, Y. Kompatsiaris, S. Staab and N. E. O'Connor, editors,
Proc. First International Conference on Semantics And Digital Media Technology (SAMT) , volume 4306, series LNCS, pages 56-70.
Springer, Heidelberg, 2006.
Andreas Hotho, Robert Jäschke, Christoph Schmitz and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
As the number of resources on the web exceeds by far the number ofdocuments one can track, it becomes increasingly difficult to remainup to date on ones own areas of interest. The problem becomes moresevere with the increasing fraction of multimedia data, from whichit is difficult to extract some conceptual description of theircontents.One way to overcome this problem are social bookmark tools, whichare rapidly emerging on the web. In such systems, users are settingup lightweight conceptual structures called folksonomies, andovercome thus the knowledge acquisition bottleneck. As more and morepeople participate in the effort, the use of a common vocabularybecomes more and more stable. We present an approach for discoveringtopic-specific trends within folksonomies. It is based on adifferential adaptation of the PageRank algorithm to the triadichypergraph structure of a folksonomy. The approach allows for anykind of data, as it does not rely on the internal structure of thedocuments. In particular, this allows to consider different datatypes in the same analysis step. We run experiments on a large-scalereal-world snapshot of a social bookmarking system.
TRIAS - An Algorithm for Mining Iceberg Tri-Lattices.
In:
Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 06), pages 907-911.
IEEE Computer Society, Hong Kong, 2006.
Robert Jäschke, Andreas Hotho, Christoph Schmitz, Bernhard Ganter and Gerd Stumme.
[doi]
[BibTeX]
Wege zur Entdeckung von Communities in Folksonomies.
In: S. Braß and A. Hinneburg, editors,
Proc. 18. Workshop Grundlagen von Datenbanken, pages 80-84.
Martin-Luther-Universität , Halle-Wittenberg, 2006.
Robert Jäschke, Andreas Hotho, Christoph Schmitz and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Content Aggregation on Knowledge Bases using Graph Clustering.
In: Y. Sure and J. Domingue, editors,
The Semantic Web: Research and Applications, volume 4011, series LNAI, pages 530-544.
Springer, Heidelberg, 2006.
Christoph Schmitz, Andreas Hotho, Robert Jäschke and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Mining Association Rules in Folksonomies.
In: V. Batagelj, H.-H. Bock, A. Ferligoj and A. �iberna, editors,
Data Science and Classification. Proceedings of the 10th IFCS Conf., series Studies in Classification, Data Analysis, and Knowledge Organization, pages 261-270.
Springer, Heidelberg, 2006.
Christoph Schmitz, Andreas Hotho, Robert Jäschke and Gerd Stumme.
[pdf]
[abstract]
[BibTeX]
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.
Mining Association Rules in Folksonomies.
In: V. Batagelj, H.-H. Bock, A. Ferligoj and A. �iberna, editors,
Data Science and Classification. Proceedings of the 10th IFCS Conf., series Studies in Classification, Data Analysis, and Knowledge Organization, pages 261-270.
Springer, Heidelberg, 2006.
Christoph Schmitz, Andreas Hotho, Robert J�schke and Gerd Stumme.
[pdf]
[abstract]
[BibTeX]
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.
Mining Association Rules in Folksonomies.
In: V. Batagelj, H.-H. Bock, A. Ferligoj and A. Žiberna, editors,
Data Science and Classification. Proceedings of the 10th IFCS Conf., series Studies in Classification, Data Analysis, and Knowledge Organization, pages 261-270.
Springer, Heidelberg, 2006.
Christoph Schmitz, Andreas Hotho, Robert Jäschke and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Proceedings of the First Workshop on Semantic Network Analysis .
CEUR Proceedings, Aachen, 2005.
Gerd Stumme, Bettina Hoser, Christoph Schmitz and Harith Alani.
[doi]
[BibTeX]
Proceedings of the First Workshop on Semantic Network Analysis .
CEUR Proceedings, Aachen, 2005.
Gerd Stumme, Bettina Hoser, Christoph Schmitz and Harith Alani.
[doi]
[BibTeX]
Document Retrieval for Email Search and Discovery using Formal Concept Analysis.
Journal of Applied Artificial Intelligence (AAI), 17(3):257-280, 2003.
Richard J. Cole, Peter W. Eklund and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
This paper discusses an document discovery tool based on
conceptual clustering by formal concept analysis. The program
allows users to navigate email using a visual lattice metaphor
rather than a tree. It implements a virtual file structure over
email where files and entire directories can appear in multiple
positions. The content and shape of the lattice formed by the
conceptual ontology can assist in email discovery. The system
described provides more flexibility in retrieving stored emails
than what is normally available in email clients. The paper
discusses how conceptual ontologies can leverage traditional
document retrieval systems and aid knowledge discovery in document
collections.