@article{jaeschke2008discovering,
  abstract = {Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples.},
  address = {New York},
  author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd},
  booktitle = {Semantic Web and Web 2.0},
  doi = {10.1016/j.websem.2007.11.004},
  editor = {Finin, T. and Mizoguchi, R. and Staab, S.},
  interhash = {cfca594f9dbe30694bfbcdeb40dc4e88},
  intrahash = {18e8babe208fae2c0342438617b0ec31},
  issn = {1570-8268},
  journal = {Web Semantics: Science, Services and Agents on the World Wide Web},
  month = feb,
  number = 1,
  pages = {38--53},
  publisher = {Elsevier},
  title = {Discovering Shared Conceptualizations in Folksonomies},
  url = {http://www.kde.cs.uni-kassel.de/pub/pdf/jaeschke2008discovering.pdf},
  vgwort = {59},
  volume = 6,
  year = 2008
}

@inproceedings{jaeschke07tagKdml,
  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 present two tag recommendation algorithms: an adaptation of user-based collaborative filtering and a graph-based recommender built on top of FolkRank, an adaptation of the well-known PageRank algorithm that can cope with undirected triadic hyperedges. We evaluate and compare both algorithms on large-scale real life datasets and show that both provide better results than non-personalized baseline methods. Especially the graph-based recommender outperforms existing methods considerably.},
  author = {Jäschke, Robert and Marinho, Leandro and Hotho, Andreas and Schmidt-Thieme, Lars and Stumme, Gerd},
  booktitle = {Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007)},
  editor = {Hinneburg, Alexander},
  interhash = {7e212e3bac146d406035adebff248371},
  intrahash = {bfc43dfe59f9c0935ac3364b12e6d795},
  isbn = {978-3-86010-907-6},
  month = sep,
  pages = {13-20},
  publisher = {Martin-Luther-Universität Halle-Wittenberg},
  title = {Tag Recommendations in Folksonomies},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2007/jaeschke07tagrecommendationsKDML.pdf},
  vgwort = {20},
  year = 2007
}

@inproceedings{jaeschke2007tag,
  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 two recommendation algorithms on largescale real life datasets: an adaptation of user-based collaborative filtering and a graph-based recommender built on top of FolkRank. We show that both provide better results than non-personalized baseline methods. Especially the graph-based recommender outperforms existing methods considerably.},
  address = {Berlin, Heidelberg},
  author = {Jäschke, Robert and Balby Marinho, Leandro and Hotho, Andreas and Schmidt-Thieme, Lars and Stumme, Gerd},
  booktitle = {Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases},
  editor = {Kok, Joost N. and Koronacki, Jacek and de Mántaras, Ramon López and Matwin, Stan and Mladenic, Dunja and Skowron, Andrzej},
  ee = {http://dx.doi.org/10.1007/978-3-540-74976-9_52},
  interhash = {7e212e3bac146d406035adebff248371},
  intrahash = {bb8ecec699a2f129322fe334747c6aef},
  isbn = {978-3-540-74975-2},
  pages = {506-514},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  title = {Tag Recommendations in Folksonomies},
  url = {http://dx.doi.org/10.1007/978-3-540-74976-9_52},
  vgwort = {14},
  volume = 4702,
  year = 2007
}