@incollection{LA:12,
  address = {Heidelberg, Germany},
  alteditor = {Editor},
  author = {Lemmerich, Florian and Atzmueller, Martin},
  booktitle = {{Modeling and Mining Ubiquitous Social Media}},
  interhash = {ae9dc5bfe7f42f1e9ca59aadda4bfd9e},
  intrahash = {8435f029bf0e32340e2cf44d0eeb65e7},
  publisher = {Springer Verlag},
  series = {LNAI},
  title = {{Describing Locations using Tags and Images: Explorative Pattern Mining in Social Media}},
  url = {http://www.kde.cs.uni-kassel.de/atzmueller/paper/lemmerich-explorative-pattern-mining-socia-media-lnai-2012.pdf},
  volume = 7472,
  year = 2012
}

@article{jaeschke2008tag,
  abstract = {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 several recommendation algorithms on large-scale real life datasets: an adaptation of
user-based collaborative filtering, a graph-based recommender built on top of the FolkRank algorithm, and simple methods based on counting tag occurences.  We show that both FolkRank and Collaborative Filtering provide better results than non-personalized baseline methods. Moreover, since methods based on counting tag occurrences are computationally cheap, and thus usually preferable for real time scenarios, we discuss simple approaches for improving the performance of such methods. We show, how a simple recommender based on counting tags from users and resources can perform almost as good as the best recommender.
},
  address = {Amsterdam},
  author = {Jäschke, Robert and Marinho, Leandro and Hotho, Andreas and Schmidt-Thieme, Lars and Stumme, Gerd},
  doi = {10.3233/AIC-2008-0438},
  editor = {Giunchiglia, Enrico},
  interhash = {b2f1aba6829affc85d852ea93a8e39f7},
  intrahash = {955bcf14f3272ba6eaf3dadbef6c0b10},
  issn = {0921-7126},
  journal = {AI Communications},
  number = 4,
  pages = {231-247},
  publisher = {IOS Press},
  title = {Tag Recommendations in Social Bookmarking Systems},
  url = {http://dx.doi.org/10.3233/AIC-2008-0438},
  vgwort = {63},
  volume = 21,
  year = 2008
}

@inproceedings{hotho2006entstehen,
  abstract = {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.},
  address = {Baden-Baden},
  author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Social Software in der Wertschöpfung},
  interhash = {1b39e4a77cac919f9030601711aad543},
  intrahash = {a333df6fdc7ff9322e3ce03988a7965e},
  publisher = {Nomos},
  title = {Das Entstehen von Semantik in BibSonomy},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006entstehen.pdf},
  year = 2006
}

@misc{golder05structure,
  author = {Golder, Scott and Huberman, Bernardo A.},
  citeulike-article-id = {305755},
  eprint = {cs.DL/0508082},
  interhash = {2d312240f16eba52c5d73332bc868b95},
  intrahash = {f852d7a909fa3edceb04abb7d2a20f71},
  month = Aug,
  priority = {2},
  title = {The Structure of Collaborative Tagging Systems},
  url = {http://arxiv.org/abs/cs.DL/0508082},
  year = 2005
}