@inproceedings{mueller2013recommendations,
  abstract = {With the rising popularity of smart mobile devices, sensor data-based
 applications have become more and more popular. Their users record
 data during their daily routine or specifically for certain events.
 The application WideNoise Plus allows users to record sound samples
 and to annotate them with perceptions and tags. The app is being
 used to document and map the soundscape all over the world. The procedure
 of recording, including the assignment of tags, has to be as easy-to-use
 as possible. We therefore discuss the application of tag recommender
 algorithms in this particular scenario. We show, that this task is
 fundamentally different from the well-known tag recommendation problem
 in folksonomies as users do no longer tag fix resources but rather
 sensory data and impressions. The scenario requires efficient recommender
 algorithms that are able to run on the mobile device, since Internet
 connectivity cannot be assumed to be available. Therefore, we evaluate
 the performance of several tag recommendation algorithms and discuss
 their applicability in the mobile sensing use-case.},
  author = {Mueller, Juergen and Doerfel, Stephan and Becker, Martin and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China -- October 12-16, 2013. Proceedings},
  interhash = {23d1cf49208d9a0c8b883dc69d4e444d},
  intrahash = {6190d6064dfdb3b8d71f2898539e993e},
  note = {accepted for publication},
  pages = {New York, NY, USA},
  publisher = {ACM},
  title = {Tag Recommendations for SensorFolkSonomies},
  year = 2013
}

@article{landia2013deeper,
  abstract = {The information contained in social tagging systems is often modelled as a graph of connections between users, items and tags. Recommendation algorithms such as FolkRank, have the potential to leverage complex relationships in the data, corresponding to multiple hops in the graph. We present an in-depth analysis and evaluation of graph models for social tagging data and propose novel adaptations and extensions of FolkRank to improve tag recommendations. We highlight implicit assumptions made by the widely used folksonomy model, and propose an alternative and more accurate graph-representation of the data. Our extensions of FolkRank address the new item problem by incorporating content data into the algorithm, and significantly improve prediction results on unpruned datasets. Our adaptations address issues in the iterative weight spreading calculation that potentially hinder FolkRank's ability to leverage the deep graph as an information source. Moreover, we evaluate the benefit of considering each deeper level of the graph, and present important insights regarding the characteristics of social tagging data in general. Our results suggest that the base assumption made by conventional weight propagation methods, that closeness in the graph always implies a positive relationship, does not hold for the social tagging domain.},
  author = {Landia, Nikolas and Doerfel, Stephan and Jäschke, Robert and Anand, Sarabjot Singh and Hotho, Andreas and Griffiths, Nathan},
  interhash = {e8095b13630452ce3ecbae582f32f4bc},
  intrahash = {e585a92994be476480545eb62d741642},
  journal = {cs.IR},
  title = {Deeper Into the Folksonomy Graph: FolkRank Adaptations and Extensions for Improved Tag Recommendations},
  url = {http://arxiv.org/abs/1310.1498},
  volume = {1310.1498},
  year = 2013
}

@inproceedings{doerfel2013analysis,
  abstract = {Since the rise of collaborative tagging systems on the web, the tag recommendation task -- suggesting suitable tags to users of such systems while they add resources to their collection -- has been tackled. However, the (offline) evaluation of tag recommendation algorithms usually suffers from difficulties like the sparseness of the data or the cold start problem for new resources or users. Previous studies therefore often used so-called post-cores (specific subsets of the original datasets) for their experiments. In this paper, we conduct a large-scale experiment in which we analyze different tag recommendation algorithms on different cores of three real-world datasets. We show, that a recommender's performance depends on the particular core and explore correlations between performances on different cores.},
  acmid = {2507222},
  address = {New York, NY, USA},
  author = {Doerfel, Stephan and Jäschke, Robert},
  booktitle = {Proceedings of the 7th ACM conference on Recommender systems},
  doi = {10.1145/2507157.2507222},
  interhash = {3eaf2beb1cdad39b7c5735a82c3338dd},
  intrahash = {aa4b3d79a362d7415aaa77625b590dfa},
  isbn = {978-1-4503-2409-0},
  location = {Hong Kong, China},
  numpages = {4},
  pages = {343--346},
  publisher = {ACM},
  series = {RecSys '13},
  title = {An analysis of tag-recommender evaluation procedures},
  url = {https://www.kde.cs.uni-kassel.de/pub/pdf/doerfel2013analysis.pdf},
  year = 2013
}

@book{balbymarinho2012recommender,
  abstract = {Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the “noise” that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.},
  author = {Balby Marinho, L. and Hotho, A. and Jäschke, R. and Nanopoulos, A. and Rendle, S. and Schmidt-Thieme, L. and Stumme, G. and Symeonidis, P.},
  doi = {10.1007/978-1-4614-1894-8},
  interhash = {0bb7f0588cd690d67cc73e219a3a24fa},
  intrahash = {87d6883ebd98e8810be45d7e7e4ade96},
  isbn = {978-1-4614-1893-1},
  month = feb,
  publisher = {Springer},
  series = {SpringerBriefs in Electrical and Computer Engineering},
  title = {Recommender Systems for Social Tagging Systems},
  url = {http://link.springer.com/book/10.1007/978-1-4614-1894-8},
  year = 2012
}

@incollection{jaeschke2012challenges,
  abstract = {Originally introduced by social bookmarking systems, collaborative tagging, or social tagging, has been widely adopted by many web-based systems like wikis, e-commerce platforms, or social networks. Collaborative tagging systems allow users to annotate resources using freely chosen keywords, so called tags . Those tags help users in finding/retrieving resources, discovering new resources, and navigating through the system. The process of tagging resources is laborious. Therefore, most systems support their users by tag recommender components that recommend tags in a personalized way. The Discovery Challenges 2008 and 2009 of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) tackled the problem of tag recommendations in collaborative tagging systems. Researchers were invited to test their methods in a competition on datasets from the social bookmark and publication sharing system BibSonomy. Moreover, the 2009 challenge included an online task where the recommender systems were integrated into BibSonomy and provided recommendations in real time. In this chapter we review, evaluate and summarize the submissions to the two Discovery Challenges and thus lay the groundwork for continuing research in this area.},
  address = {Berlin/Heidelberg},
  affiliation = {Knowledge & Data Engineering Group, University of Kassel, Wilhelmshöher Allee 73, 34121 Kassel, Germany},
  author = {Jäschke, Robert and Hotho, Andreas and Mitzlaff, Folke and Stumme, Gerd},
  booktitle = {Recommender Systems for the Social Web},
  doi = {10.1007/978-3-642-25694-3_3},
  editor = {Pazos Arias, José J. and Fernández Vilas, Ana and Díaz Redondo, Rebeca P.},
  interhash = {75b1a6f54ef54d0126d0616b5bf77563},
  intrahash = {7d41d332cccc3e7ba8e7dadfb7996337},
  isbn = {978-3-642-25694-3},
  pages = {65--87},
  publisher = {Springer},
  series = {Intelligent Systems Reference Library},
  title = {Challenges in Tag Recommendations for Collaborative Tagging Systems},
  url = {http://dx.doi.org/10.1007/978-3-642-25694-3_3},
  volume = 32,
  year = 2012
}

@inproceedings{illig2009comparison,
  abstract = {Recommendation algorithms and multi-class classifiers can support
users of social bookmarking systems in assigning tags to their
bookmarks. Content based recommenders are the usual approach for
facing the cold start problem, i.e., when a bookmark is uploaded for
the first time and no information from other users can be exploited.
In this paper, we evaluate several recommendation algorithms in a
cold-start scenario on a large real-world dataset.
},
  address = {Berlin/Heidelberg},
  author = {Illig, Jens and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd},
  booktitle = {Knowledge Processing and Data Analysis},
  doi = {10.1007/978-3-642-22140-8_9},
  editor = {Wolff, Karl Erich and Palchunov, Dmitry E. and Zagoruiko, Nikolay G. and Andelfinger, Urs},
  interhash = {cd3420c0f73761453320dc528b3d1e14},
  intrahash = {f9d6e06ab0f2fdcebb77afa97d72e40a},
  isbn = {978-3-642-22139-2},
  pages = {136--149},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  title = {A Comparison of Content-Based Tag Recommendations in Folksonomy Systems},
  url = {http://dx.doi.org/10.1007/978-3-642-22140-8_9},
  volume = 6581,
  year = 2011
}

@inproceedings{illig2011comparison,
  author = {Illig, Jens and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd},
  booktitle = {Postproceedings of the International Conference on Knowledge Processing in Practice (KPP 2007)},
  interhash = {cd3420c0f73761453320dc528b3d1e14},
  intrahash = {0a4a7f95efa9493d804816bb75ecbf33},
  publisher = {Springer},
  title = {A Comparison of content-based Tag Recommendations in Folksonomy Systems},
  year = 2011
}

@inproceedings{schmitz07network,
  address = {Banff},
  author = {Schmitz, Christoph and Grahl, Miranda and Hotho, Andreas and Stumme, Gerd and Catutto, Ciro and Baldassarri, Andrea and Loreto, Vittorio and Servedio, Vito D. P.},
  booktitle = {Proc. WWW2007 Workshop ``Tagging and Metadata for Social Information Organization''},
  day = 8,
  interhash = {20bd468c1c9b71206ac6f8b67ed676d6},
  intrahash = {23a0a0cd67ab0014e0346527e986caeb},
  month = may,
  title = {Network Properties of Folksonomies},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2007/schmitz07network.pdf},
  year = 2007
}

@inproceedings{jaeschke2007analysis,
  abstract = {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.},
  address = {Berlin, Heidelberg},
  author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Proceedings of the 15th International Conference on Conceptual Structures (ICCS 2007)},
  editor = {Priss, U. and Polovina, S. and Hill, R.},
  interhash = {4352d1142afa561460511b22d4ce5103},
  intrahash = {0c2b212b9ea3d822bf4729fd5fe6b6e1},
  isbn = {3-540-73680-8},
  month = {July},
  pages = {283--295},
  publisher = {Springer-Verlag},
  series = {Lecture Notes in Artificial Intelligence},
  title = {Analysis of the Publication Sharing Behaviour in {BibSonomy}},
  volume = 4604,
  year = 2007
}

@inproceedings{jaeschke07tagKdml,
  author = {Jaeschke, 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 = {19e40fd1eb137fab091512656ecc504d},
  intrahash = {71bc9f8ae1a53632dc9a2b98b017f152},
  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},
  year = 2007
}

@inproceedings{hotho2006trend,
  abstract = {As the number of resources on the web exceeds by far the number ofdocuments one can track, it becomes increasingly difficult to remainup to date on ones own areas of interest. The problem becomes moresevere with the increasing fraction of multimedia data, from whichit is difficult to extract some conceptual description of theircontents.One way to overcome this problem are social bookmark tools, whichare rapidly emerging on the web. In such systems, users are settingup lightweight conceptual structures called folksonomies, andovercome thus the knowledge acquisition bottleneck. As more and morepeople participate in the effort, the use of a common vocabularybecomes more and more stable. We present an approach for discoveringtopic-specific trends within folksonomies. It is based on adifferential adaptation of the PageRank algorithm to the triadichypergraph structure of a folksonomy. The approach allows for anykind of data, as it does not rely on the internal structure of thedocuments. In particular, this allows to consider different datatypes in the same analysis step. We run experiments on a large-scalereal-world snapshot of a social bookmarking system.},
  address = {Heidelberg},
  author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Proc. First International Conference on Semantics And Digital Media Technology (SAMT) },
  editor = {Avrithis, Yannis S. and Kompatsiaris, Yiannis and Staab, Steffen and O'Connor, Noel E.},
  ee = {http://dx.doi.org/10.1007/11930334_5},
  interhash = {227be738c5cea57530d592463fd09abd},
  intrahash = {42cda5911e901eadd0ac6a106a6aa1dc},
  isbn = {3-540-49335-2},
  month = {December},
  pages = {56-70},
  publisher = {Springer},
  series = {LNCS},
  title = {Trend Detection in Folksonomies},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006trend.pdf},
  vgwort = {27},
  volume = 4306,
  year = 2006
}

@article{cattuto2007networkb,
  author = {Cattuto, Ciro and Schmitz, Christoph and Baldassarri, Andrea and Servedio, Vito D. P. and Loreto, Vittorio and Hotho, Andreas and Grahl, Miranda and Stumme, Gerd},
  editor = {Hoche, Susanne and Nürnberger, Andreas and Flach, Jürgen},
  interhash = {fc5f2df61d28bc99b7e15029da125588},
  intrahash = {da6c676c5664017247c7564fc247b190},
  issn = {0921-7126},
  journal = {AI Communications Journal, Special Issue on ``Network Analysis in Natural Sciences and Engineering''},
  number = 4,
  pages = {245-262},
  publisher = {IOS Press},
  title = {Network Properties of Folksonomies},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2007/cattuto2007network.pdf},
  vgwort = {67},
  volume = 20,
  year = 2007
}

@inproceedings{hotho2006emergent,
  abstract = {Social bookmark tools are rapidly emerging on the Web. In suchsystems users are setting up lightweight conceptual structurescalled folksonomies. The reason for their immediate success is thefact that no specific skills are needed for participating. In thispaper we specify a formal model for folksonomies, briefly describeour own system BibSonomy, which allows for sharing both bookmarks andpublication references, and discuss first steps towards emergent semantics.},
  address = {Bonn},
  author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Informatik 2006 -- Informatik für Menschen. Band 2},
  editor = {Hochberger, Christian and Liskowsky, Rüdiger},
  file = {hotho2006emergent.pdf:hotho2006emergent.pdf:PDF},
  groups = {public},
  interhash = {53e5677ab0bf1a8f5a635cc32c9082ba},
  intrahash = {05043cc20f1e0f5a612135c970e4f1ac},
  month = {October},
  note = {Proc. Workshop on Applications of Semantic Technologies, Informatik 2006},
  publisher = {Gesellschaft für Informatik},
  series = {Lecture Notes in Informatics},
  title = {Emergent Semantics in BibSonomy},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006emergent.pdf},
  username = {dbenz},
  volume = {P-94},
  year = 2006
}

@inproceedings{hotho2006trend,
  abstract = {As the number of resources on the web exceeds by far the number ofdocuments one can track, it becomes increasingly difficult to remainup to date on ones own areas of interest. The problem becomes moresevere with the increasing fraction of multimedia data, from whichit is difficult to extract some conceptual description of theircontents.One way to overcome this problem are social bookmark tools, whichare rapidly emerging on the web. In such systems, users are settingup lightweight conceptual structures called folksonomies, andovercome thus the knowledge acquisition bottleneck. As more and morepeople participate in the effort, the use of a common vocabularybecomes more and more stable. We present an approach for discoveringtopic-specific trends within folksonomies. It is based on adifferential adaptation of the PageRank algorithm to the triadichypergraph structure of a folksonomy. The approach allows for anykind of data, as it does not rely on the internal structure of thedocuments. In particular, this allows to consider different datatypes in the same analysis step. We run experiments on a large-scalereal-world snapshot of a social bookmarking system.},
  address = {Heidelberg},
  author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Proc. First International Conference on Semantics And Digital Media Technology (SAMT) },
  date = {2006-12-13},
  editor = {Avrithis, Yannis S. and Kompatsiaris, Yiannis and Staab, Steffen and O'Connor, Noel E.},
  ee = {http://dx.doi.org/10.1007/11930334_5},
  interhash = {227be738c5cea57530d592463fd09abd},
  intrahash = {42cda5911e901eadd0ac6a106a6aa1dc},
  isbn = {3-540-49335-2},
  month = {December},
  pages = {56-70},
  publisher = {Springer},
  series = {LNCS},
  title = {Trend Detection in Folksonomies},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006trend.pdf},
  vgwort = {27},
  volume = 4306,
  year = 2006
}

@inproceedings{hotho2006bibsonomy,
  abstract = {Social bookmark tools are rapidly emerging on the Web. In suchsystems users are setting up lightweight conceptual structurescalled folksonomies. The reason for their immediate success is thefact that no specific skills are needed for participating. In thispaper we specify a formal model for folksonomies and briefly describe our own system BibSonomy, which allows for sharing both bookmarksand publication references in a kind of personal library.},
  address = {Aalborg},
  author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Proceedings of the First Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures},
  editor = {de Moor, Aldo and Polovina, Simon and Delugach, Harry},
  file = {hotho2006bibsonomy.pdf:hotho2006bibsonomy.pdf:PDF},
  interhash = {d28c9f535d0f24eadb9d342168836199},
  intrahash = {5854a71547051543dd3d3d5e2e2f2b67},
  isbn = {87-7307-769-0},
  pages = {87-102},
  publisher = {Aalborg Universitetsforlag},
  title = {{BibSonomy}: A Social Bookmark and Publication Sharing System},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006bibsonomy.pdf},
  year = 2006
}

@article{cattuto2007networkb,
  author = {Cattuto, Ciro and Schmitz, Christoph and Baldassarri, Andrea and Servedio, Vito D. P. and Loreto, Vittorio and Hotho, Andreas and Grahl, Miranda and Stumme, Gerd},
  editor = {Hoche, Susanne and Nürnberger, Andreas and Flach, Jürgen},
  interhash = {fc5f2df61d28bc99b7e15029da125588},
  intrahash = {da6c676c5664017247c7564fc247b190},
  issn = {0921-7126},
  journal = {AI Communications Journal, Special Issue on ``Network Analysis in Natural Sciences and Engineering''},
  number = 4,
  pages = {245-262},
  publisher = {IOS Press},
  title = {Network Properties of Folksonomies},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2007/cattuto2007network.pdf},
  vgwort = {67},
  volume = 20,
  year = 2007
}

@inproceedings{hotho2006emergent,
  abstract = {Social bookmark tools are rapidly emerging on the Web. In suchsystems users are setting up lightweight conceptual structurescalled folksonomies. The reason for their immediate success is thefact that no specific skills are needed for participating. In thispaper we specify a formal model for folksonomies, briefly describeour own system BibSonomy, which allows for sharing both bookmarks andpublication references, and discuss first steps towards emergent semantics.},
  address = {Bonn},
  author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Informatik 2006 -- Informatik für Menschen. Band 2},
  editor = {Hochberger, Christian and Liskowsky, Rüdiger},
  file = {hotho2006emergent.pdf:hotho2006emergent.pdf:PDF},
  groups = {public},
  interhash = {53e5677ab0bf1a8f5a635cc32c9082ba},
  intrahash = {05043cc20f1e0f5a612135c970e4f1ac},
  month = {October},
  note = {Proc. Workshop on Applications of Semantic Technologies, Informatik 2006},
  publisher = {Gesellschaft für Informatik},
  series = {Lecture Notes in Informatics},
  timestamp = {2009-09-14 18:13:04},
  title = {Emergent Semantics in BibSonomy},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006emergent.pdf},
  username = {dbenz},
  volume = {P-94},
  year = 2006
}

@inproceedings{hotho2006information,
  abstract = {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 findcommunities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset.},
  address = {Heidelberg},
  author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {The Semantic Web: Research and Applications},
  editor = {Sure, York and Domingue, John},
  file = {hotho2006information.pdf:hotho2006information.pdf:PDF},
  groups = {public},
  interhash = {10ec64d80b0ac085328a953bb494fb89},
  intrahash = {3c301945817681d637ee43901c016939},
  month = {June},
  pages = {411-426},
  pdf = {hotho2006information.pdf},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  timestamp = {2010-11-11 15:34:51},
  title = {Information Retrieval in Folksonomies: Search and Ranking},
  username = {dbenz},
  volume = 4011,
  year = 2006
}

@inproceedings{jaeschke2007analysis,
  abstract = {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.},
  address = {Berlin, Heidelberg},
  author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Proceedings of the 15th International Conference on Conceptual Structures (ICCS 2007)},
  editor = {Priss, U. and Polovina, S. and Hill, R.},
  file = {jaeschke2007analysis.pdf:jaeschke2007analysis.pdf:PDF},
  groups = {public},
  interhash = {4352d1142afa561460511b22d4ce5103},
  intrahash = {0c2b212b9ea3d822bf4729fd5fe6b6e1},
  isbn = {3-540-73680-8},
  month = {July},
  pages = {283--295},
  publisher = {Springer-Verlag},
  series = {Lecture Notes in Artificial Intelligence},
  timestamp = {2010-11-10 15:35:25},
  title = {Analysis of the Publication Sharing Behaviour in {BibSonomy}},
  username = {dbenz},
  vgwort = {22},
  volume = 4604,
  year = 2007
}

@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.},
  file = {jaeschke2008discovering.pdf:jaeschke2008discovering.pdf:PDF},
  groups = {public},
  interhash = {cfca594f9dbe30694bfbcdeb40dc4e88},
  intrahash = {18e8babe208fae2c0342438617b0ec31},
  issn = {1570-8268},
  journal = {Web Semantics: Science, Services and Agents on the World Wide Web},
  journalpub = {1},
  month = feb,
  number = 1,
  pages = {38--53},
  publisher = {Elsevier},
  timestamp = {2010-11-10 15:35:25},
  title = {Discovering Shared Conceptualizations in Folksonomies},
  url = {http://www.sciencedirect.com/science/article/B758F-4R53WD4-1/2/ae56bd6e7132074272ca2035be13781b},
  username = {dbenz},
  vgwort = {59},
  volume = 6,
  year = 2008
}