@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{jaeschke2008logsonomy,
  abstract = {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.},
  author = {Jäschke, Robert and Krause, Beate and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)},
  interhash = {13ec3f45fc7e0364cdc6b9a7c12c5c2c},
  intrahash = {359e1eccdc524334d4a2ad51330f76ae},
  publisher = {AAAI Press},
  title = {Logsonomy -- A Search Engine Folksonomy},
  url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2008/Krause2008logsonomy_short.pdf},
  year = 2008
}

@inproceedings{krause2008comparison,
  address = {Glasgow, UK},
  author = {Krause, Beate and Hotho, Andreas and Stumme, Gerd},
  booktitle = {30th European Conference on IR Research, ECIR 2008},
  editor = {Macdonald, Craig and Ounis, Iadh and Plachouras, Vassilis and Ruthven, Ian and White, Ryen W.},
  interhash = {37598733b747093d97a0840a11beebf5},
  intrahash = {ad5f4664d1f5b967a0793b4a26a0edbb},
  isbn = {978-3-540-78645-0},
  misc = {vgwort=21,1},
  month = {April},
  pages = {101-113},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  title = {A Comparison of Social Bookmarking with Traditional Search},
  volume = 4956,
  year = 2008
}

@inproceedings{benz2009characterizing,
  address = {Bled, Slovenia},
  author = {Benz, Dominik and Krause, Beate and Kumar, G. Praveen and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Proceedings of the 1st Workshop on Explorative Analytics of Information Networks (EIN2009)},
  file = {benz2009characterizing.pdf:benz2009characterizing.pdf:PDF},
  groups = {public},
  interhash = {de5e58b26200e44112d9791f39e7523d},
  intrahash = {b697a98a7340585594455ee2e81d238a},
  month = {September},
  title = {Characterizing Semantic Relatedness of Search Query Terms},
  url = {http://www.kde.cs.uni-kassel.de/pub/pdf/benz2009characterizing.pdf},
  username = {dbenz},
  year = 2009
}