TY  - JOUR
AU  - Benz, Dominik
AU  - Hotho, Andreas
AU  - Jäschke, Robert
AU  - Krause, Beate
AU  - Mitzlaff, Folke
AU  - Schmitz, Christoph
AU  - Stumme, Gerd
T1  - The Social Bookmark and Publication Management System Bibsonomy
JO  - The VLDB Journal
PY  - 2010/12
VL  - 19
IS  - 6
SP  - 849
EP  - 875
UR  - http://dx.doi.org/10.1007/s00778-010-0208-4
DO  - 10.1007/s00778-010-0208-4
KW  - publicationmanagment
KW  - bookmark
KW  - publikationsmanagment
KW  - social
KW  - myown
KW  - bibsonomy
KW  - publication
KW  - management
L1  - 
SN  - 
N1  - The social bookmark and publication management system bibsonomy
N1  - 
AB  - Social resource sharing systems are central elements of the Web 2.0 and use the same kind of lightweight knowledge representation, called folksonomy. Their large user communities and ever-growing networks of user-generated content have made them an attractive object of investigation for researchers from different disciplines like Social Network Analysis, Data Mining, Information Retrieval or Knowledge Discovery. In this paper, we summarize and extend our work on different aspects of this branch of Web 2.0 research, demonstrated and evaluated within our own social bookmark and publication sharing system BibSonomy, which is currently among the three most popular systems of its kind. We structure this presentation along the different interaction phases of a user with our system, coupling the relevant research questions of each phase with the corresponding implementation issues. This approach reveals in a systematic fashion important aspects and results of the broad bandwidth of folksonomy research like capturing of emergent semantics, spam detection, ranking algorithms, analogies to search engine log data, personalized tag recommendations and information extraction techniques. We conclude that when integrating a real-life application like BibSonomy into research, certain constraints have to be considered; but in general, the tight interplay between our scientific work and the running system has made BibSonomy a valuable platform for demonstrating and evaluating Web 2.0 research.
ER  -

TY  - CONF
AU  - Jäschke, Robert
AU  - Hotho, Andreas
AU  - Schmitz, Christoph
AU  - Stumme, Gerd
A2  - Priss, U.
A2  - Polovina, S.
A2  - Hill, R.
T1  - Analysis of the Publication Sharing Behaviour in BibSonomy
T2  - Proceedings of the 15th International Conference on Conceptual Structures (ICCS 2007)
PB  - Springer-Verlag
C1  - Berlin, Heidelberg
PY  - 2007/07
CY  -  
VL  - 4604
IS  - 
SP  - 283
EP  - 295
UR  - 
DO  - 
KW  - 2007
KW  - dfg
KW  - trias
KW  - social
KW  - analysis
KW  - folksonomy
KW  - bookmarking
KW  - fca
KW  - iccs
KW  - bibsonomy
L1  - 
SN  - 
N1  - Antrag dfg Literatur 
N1  - 
AB  - 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.
ER  -

TY  - CONF
AU  - Hotho, Andreas
AU  - J�schke, Robert
AU  - Schmitz, Christoph
AU  - Stumme, Gerd
A2  - Sure, York
A2  - Domingue, John
T1  - Information Retrieval in Folksonomies: Search and Ranking
T2  - The Semantic Web: Research and Applications
PB  - Springer
C1  - Heidelberg
PY  - 2006/06
CY  -  
VL  - 4011
IS  - 
SP  - 411
EP  - 426
UR  - http://.kde.cs.uni-kassel.de/hotho
DO  - 
KW  - closely_related
KW  - ranking
KW  - diploma_thesis
KW  - search
KW  - folkrank
KW  - bibsonomy
L1  - hotho06-information.pdf
SN  - 
N1  - 
N1  - 
AB  - 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.
ER  -