JabRef References output

Author	Title	Year	Journal/Proceedings	Reftype	DOI/URL
Atzmueller, M.	Mining Social Media: Key Players, Sentiments, and Communities [BibTeX]	2012	WIREs: Data Mining and Knowledge Discovery Vol. In Press	article
BibTeX: @article{Atzmueller:12c, author = {Atzmueller, Martin}, title = {Mining Social Media: Key Players, Sentiments, and Communities}, journal = {WIREs: Data Mining and Knowledge Discovery}, year = {2012}, volume = {In Press} }
Bullock, B.N., Lerch, H., Ro A., Hotho, A. & Stumme, G.	Privacy-aware spam detection in social bookmarking systems [Abstract] [BibTeX]	2011	Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies, pp. 15:1-15:8	inproceedings	DOI URL
Abstract: With the increased popularity of Web 2.0 services in the last years data privacy has become a major concern for users. The more personal data users reveal, the more difficult it becomes to control its disclosure in the web. However, for Web 2.0 service providers, the data provided by users is a valuable source for offering effective, personalised data mining services. One major application is the detection of spam in social bookmarking systems: in order to prevent a decrease of content quality, providers need to distinguish spammers and exclude them from the system. They thereby experience a conflict of interests: on the one hand, they need to identify spammers based on the information they collect about users, on the other hand, they need to respect privacy concerns and process as few personal data as possible. It would therefore be of tremendous help for system developers and users to know which personal data are needed for spam detection and which can be ignored. In this paper we address these questions by presenting a data privacy aware feature engineering approach. It consists of the design of features for spam classification which are evaluated according to both, performance and privacy conditions. Experiments using data from the social bookmarking system BibSonomy show that both conditions must not exclude each other.
BibTeX: @inproceedings{bullock2011privacyaware, author = {Bullock, Beate Navarro and Lerch, Hana and Ro Alexander and Hotho, Andreas and Stumme, Gerd}, title = {Privacy-aware spam detection in social bookmarking systems}, booktitle = {Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies}, publisher = {ACM}, year = {2011}, pages = {15:1--15:8}, url = {http://doi.acm.org/10.1145/2024288.2024306}, doi = {http://dx.doi.org/10.1145/2024288.2024306} }
Krause, B., Schmitz, C., Hotho, A. & Stumme, G.	The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems [Abstract] [BibTeX]	2008	AIRWeb '08: Proceedings of the 4th International Workshop on Adversarial Information Retrieval on the Web, pp. 61-68	inproceedings	DOI URL
Abstract: The annotation of web sites in social bookmarking systemshas become a popular way to manage and find informationon the web. The community structure of such systems attractsspammers: recent post pages, popular pages or specifictag pages can be manipulated easily. As a result, searchingor tracking recent posts does not deliver quality resultsannotated in the community, but rather unsolicited, oftencommercial, web sites. To retain the benefits of sharingone’s web content, spam-fighting mechanisms that can facethe flexible strategies of spammers need to be developed.
BibTeX: @inproceedings{krause2008antisocial, author = {Krause, Beate and Schmitz, Christoph and Hotho, Andreas and Stumme, Gerd}, title = {The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems}, booktitle = {AIRWeb '08: Proceedings of the 4th International Workshop on Adversarial Information Retrieval on the Web}, publisher = {ACM}, year = {2008}, pages = {61--68}, url = {http://airweb.cse.lehigh.edu/2008/submissions/krause_2008_anti_social_tagger.pdf}, doi = {http://dx.doi.org/10.1145/1451983.1451998} }
Falkowski, T., Barth, A. & Spiliopoulou, M.	DENGRAPH: A Density-based Community Detection Algorithm [BibTeX]	2007	In Proc. of the 2007 IEEE / WIC / ACM International Conference on Web Intelligence,, pp. 112-115	inproceedings	URL
BibTeX: @inproceedings{FalBarSpi07, author = {Falkowski, Tanja and Barth, Anja and Spiliopoulou, Myra}, title = {DENGRAPH: A Density-based Community Detection Algorithm}, booktitle = {In Proc. of the 2007 IEEE / WIC / ACM International Conference on Web Intelligence,}, year = {2007}, pages = {112-115}, url = {http://wwwiti.cs.uni-magdeburg.de/~tfalkows/publ/2007/WI_FalBarSpi07.pdf} }
Hotho, A., Jäschke, R., Schmitz, C. & Stumme, G.	Trend Detection in Folksonomies [Abstract] [BibTeX]	2006	Vol. 4306Proc. First International Conference on Semantics And Digital Media Technology (SAMT) , pp. 56-70	inproceedings	URL
Abstract: As the number of resources on the web exceeds by far the number of cuments one can track, it becomes increasingly difficult to remain to date on ones own areas of interest. The problem becomes more vere with the increasing fraction of multimedia data, from which is difficult to extract some conceptual description of their ntents. ne way to overcome this problem are social bookmark tools, which e rapidly emerging on the web. In such systems, users are setting lightweight conceptual structures called folksonomies, and ercome thus the knowledge acquisition bottleneck. As more and more ople participate in the effort, the use of a common vocabulary comes more and more stable. We present an approach for discovering pic-specific trends within folksonomies. It is based on a fferential adaptation of the PageRank algorithm to the triadic pergraph structure of a folksonomy. The approach allows for any nd of data, as it does not rely on the internal structure of the cuments. In particular, this allows to consider different data pes in the same analysis step. We run experiments on a large-scale al-world snapshot of a social bookmarking system.
BibTeX: @inproceedings{hotho2006trend, author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd}, title = {Trend Detection in Folksonomies}, booktitle = {Proc. First International Conference on Semantics And Digital Media Technology (SAMT) }, publisher = {Springer}, year = {2006}, volume = {4306}, pages = {56-70}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006trend.pdf} }
Jäschke, R., Hotho, A., Schmitz, C. & Stumme, G.	Wege zur Entdeckung von Communities in Folksonomies [Abstract] [BibTeX]	2006	Proc. 18. Workshop Grundlagen von Datenbanken, pp. 80-84	inproceedings	URL
Abstract: Ein wichtiger Baustein des neu entdeckten World Wide Web -- des "`Web 2.0"' -- stellen lksonomies dar. In diesen Systemen können Benutzer gemeinsam Ressourcen verwalten und t Schlagwörtern versehen. Die dadurch entstehenden begrifflichen Strukturen stellen n interessantes Forschungsfeld dar. Dieser Artikel untersucht Ansätze und Wege zur tdeckung und Strukturierung von Nutzergruppen ("Communities") in Folksonomies.
BibTeX: @inproceedings{jaeschke2006wege, author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Stumme, Gerd}, title = {Wege zur Entdeckung von Communities in Folksonomies}, booktitle = {Proc. 18. Workshop Grundlagen von Datenbanken}, publisher = {Martin-Luther-Universität }, year = {2006}, pages = {80-84}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/jaeschke2006wege.pdf} }
Kumar, R., Raghavan, P., Rajagopalan, S. & Tomkins, A.	Trawling the Web for emerging cyber-communities [BibTeX]	1999	Computer Networks Vol. 31(11-16), pp. 1481-1493	article	URL
BibTeX: @article{kumar99trawling, author = {Kumar, Ravi and Raghavan, Prabhakar and Rajagopalan, Sridhar and Tomkins, Andrew}, title = {Trawling the Web for emerging cyber-communities}, journal = {Computer Networks }, year = {1999}, volume = {31}, number = {11--16}, pages = {1481--1493}, url = {citeseer.ist.psu.edu/kumar99trawling.html} }

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