A Comparison of content-based Tag Recommendations in Folksonomy Systems.
In:
Postproceedings of the International Conference on Knowledge Processing in Practice (KPP 2007).
Springer, 2011.
Jens Illig, Andreas Hotho, Robert Jäschke und Gerd Stumme.
[BibTeX]
Query Logs as Folksonomies.
Datenbank-Spektrum, 10(1):15-24, 2010.
Dominik Benz, Andreas Hotho, Robert Jäschke, Beate Krause und Gerd Stumme.
[doi]
[Kurzfassung]
[BibTeX]
Query logs provide a valuable resource for preference information in search. A user clicking on a specific resource after submitting a query indicates that the resource has some relevance with respect to the query. To leverage the information ofquery logs, one can relate submitted queries from specific users to their clicked resources and build a tripartite graph ofusers, resources and queries. This graph resembles the folksonomy structure of social bookmarking systems, where users addtags to resources. In this article, we summarize our work on building folksonomies from query log files. The focus is on threecomparative studies of the system’s content, structure and semantics. Our results show that query logs incorporate typicalfolksonomy properties and that approaches to leverage the inherent semantics of folksonomies can be applied to query logsas well.
Logsonomy - A Search Engine Folksonomy.
In:
Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008).
AAAI Press, 2008.
Robert Jäschke, Beate Krause, Andreas Hotho und Gerd Stumme.
[doi]
[Kurzfassung]
[BibTeX]
In social bookmarking systems users describe bookmarksby keywords called tags. The structure behindthese social systems, called folksonomies, can beviewed as a tripartite hypergraph of user, tag and resourcenodes. This underlying network shows specificstructural properties that explain its growth and the possibilityof serendipitous exploration.Search engines filter the vast information of the web.Queries describe a user’s information need. In responseto the displayed results of the search engine, users clickon the links of the result page as they expect the answerto be of relevance. The clickdata can be represented as afolksonomy in which queries are descriptions of clickedURLs. This poster analyzes the topological characteristicsof the resulting tripartite hypergraph of queries,users and bookmarks of two query logs and compares ittwo a snapshot of the folksonomy del.icio.us.
Logsonomy - Social Information Retrieval with Logdata.
In:
HT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia, Seiten 157-166.
ACM, New York, NY, USA, 2008.
Beate Krause, Robert Jäschke, Andreas Hotho und Gerd Stumme.
[doi]
[Kurzfassung]
[BibTeX]
Social bookmarking systems constitute an established
part of the Web 2.0. In such systems
users describe bookmarks by keywords
called tags. The structure behind these social
systems, called folksonomies, can be viewed
as a tripartite hypergraph of user, tag and resource
nodes. This underlying network shows
specific structural properties that explain its
growth and the possibility of serendipitous
exploration.
Today’s search engines represent the gateway
to retrieve information from the World Wide
Web. Short queries typically consisting of
two to three words describe a user’s information
need. In response to the displayed
results of the search engine, users click on
the links of the result page as they expect
the answer to be of relevance.
This clickdata can be represented as a folksonomy
in which queries are descriptions of
clicked URLs. The resulting network structure,
which we will term logsonomy is very
similar to the one of folksonomies. In order
to find out about its properties, we analyze
the topological characteristics of the tripartite
hypergraph of queries, users and bookmarks
on a large snapshot of del.icio.us and
on query logs of two large search engines.
All of the three datasets show small world
properties. The tagging behavior of users,
which is explained by preferential attachment
of the tags in social bookmark systems, is
reflected in the distribution of single query
words in search engines. We can conclude
that the clicking behaviour of search engine
users based on the displayed search results
and the tagging behaviour of social bookmarking
users is driven by similar dynamics.
The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems.
In:
Proc. of the Fourth International Workshop on Adversarial Information Retrieval on the Web.
2008.
Beate Krause, Christoph Schmitz, Andreas Hotho und Gerd Stumme.
[doi]
[BibTeX]
Network Properties of Folksonomies.
AI Communications Journal, Special Issue on ``Network Analysis in Natural Sciences and Engineering'', 20(4):245-262, 2007.
Ciro Cattuto, Christoph Schmitz, Andrea Baldassarri, Vito D. P. Servedio, Vittorio Loreto, Andreas Hotho, Miranda Grahl und Gerd Stumme.
[doi]
[BibTeX]
Conceptual Clustering of Social Bookmark Sites.
In: A. Hinneburg
(Herausgeber):
Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007), Seiten 50-54.
Martin-Luther-Universität Halle-Wittenberg, 2007.
Miranda Grahl, Andreas Hotho und Gerd Stumme.
[doi]
[BibTeX]
Conceptual Clustering of Social Bookmarking Sites.
In:
7th International Conference on Knowledge Management (I-KNOW '07), Seiten 356-364.
Know-Center, Graz, Austria, 2007.
Miranda Grahl, Andreas Hotho und Gerd Stumme.
[doi]
[Kurzfassung]
[BibTeX]
Currently, social bookmarking systems provide intuitive support for browsing locally their content. A global view is usually presented by the tag cloud of thesystem, but it does not allow a conceptual drill-down, e. g., along a conceptual hierarchy. In this paper, we present a clustering approach for computing such a conceptual hierarchy for a given folksonomy. The hierarchy is complemented with ranked lists of users and resources most related to each cluster. The rankings are computed using our FolkRank algorithm. We have evaluated our approach on large scale data from the del.icio.us bookmarking system.
Tag Recommendations in Folksonomies.
In: A. Hinneburg
(Herausgeber):
Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007), Seiten 13-20.
Martin-Luther-Universität Halle-Wittenberg, 2007.
Robert Jaeschke, Leandro Marinho, Andreas Hotho, Lars Schmidt-Thieme und Gerd Stumme.
[doi]
[BibTeX]
Analysis of the Publication Sharing Behaviour in BibSonomy.
In: U. Priss, S. Polovina und R. Hill
(Herausgeber):
Proceedings of the 15th International Conference on Conceptual Structures (ICCS 2007), Band 4604, Reihe Lecture Notes in Artificial Intelligence, Seiten 283-295.
Springer-Verlag, Berlin, Heidelberg, 2007.
Robert Jäschke, Andreas Hotho, Christoph Schmitz und Gerd Stumme.
[Kurzfassung]
[BibTeX]
BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. In this paper we present the system, followed by a description of the insights in the structure of its bibliographic data that we gained by applying techniques we developed in the area of Formal Concept Analysis.
Network Properties of Folksonomies.
In:
Proc. WWW2007 Workshop ``Tagging and Metadata for Social Information Organization''.
Banff, 2007.
Christoph Schmitz, Miranda Grahl, Andreas Hotho, Gerd Stumme, Ciro Catutto, Andrea Baldassarri, Vittorio Loreto und Vito D. P. Servedio.
[doi]
[BibTeX]
Emergent Semantics in BibSonomy.
In: C. Hochberger und R. Liskowsky
(Herausgeber):
Informatik 2006 - Informatik für Menschen. Band 2, Band P-94, Reihe Lecture Notes in Informatics.
Gesellschaft für Informatik, Bonn, 2006.
Proc. Workshop on Applications of Semantic Technologies, Informatik 2006
Andreas Hotho, Robert Jäschke, Christoph Schmitz und Gerd Stumme.
[doi]
[Kurzfassung]
[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.
Information Retrieval in Folksonomies: Search and Ranking.
In: Y. Sure und J. Domingue
(Herausgeber):
The Semantic Web: Research and Applications, Band 4011, Reihe LNAI, Seiten 411-426.
Springer, Heidelberg, 2006.
Andreas Hotho, Robert J?schke, Christoph Schmitz und Gerd Stumme.
[BibTeX]
Information Retrieval in Folksonomies: Search and Ranking.
In: Y. Sure und J. Domingue
(Herausgeber):
The Semantic Web: Research and Applications, Band 4011, Reihe LNAI, Seiten 411-426.
Springer, Heidelberg, 2006.
Andreas Hotho, Robert Jäschke, Christoph Schmitz und Gerd Stumme.
[BibTeX]
Trend Detection in Folksonomies.
In: Y. S. Avrithis, Y. Kompatsiaris, S. Staab und N. E. O'Connor
(Herausgeber):
Proc. First International Conference on Semantics And Digital Media Technology (SAMT) , Band 4306, Reihe LNCS, Seiten 56-70.
Springer, Heidelberg, 2006.
Andreas Hotho, Robert Jäschke, Christoph Schmitz und Gerd Stumme.
[doi]
[Kurzfassung]
[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), Seiten 907-911.
IEEE Computer Society, Hong Kong, 2006.
Robert Jäschke, Andreas Hotho, Christoph Schmitz, Bernhard Ganter und Gerd Stumme.
[doi]
[BibTeX]
Mining Association Rules in Folksonomies.
In: V. Batagelj, H.-H. Bock, A. Ferligoj und A. vZiberna
(Herausgeber):
Data Science and Classification: Proc. of the 10th IFCS Conf., Reihe Studies in Classification, Data Analysis, and Knowledge Organization, Seiten 261-270.
Springer, Berlin, Heidelberg, 2006.
Christoph Schmitz, Andreas Hotho, Robert Jäschke und Gerd Stumme.
[BibTeX]