@article{benz2010query,
  abstract = {Query logs provide a valuable resource for preference information in search. A user clicking on a specific resource after submitting a query indicates that the resource has some relevance with respect to the query. To leverage the information ofquery logs, one can relate submitted queries from specific users to their clicked resources and build a tripartite graph ofusers, resources and queries. This graph resembles the folksonomy structure of social bookmarking systems, where users addtags to resources. In this article, we summarize our work on building folksonomies from query log files. The focus is on threecomparative studies of the system’s content, structure and semantics. Our results show that query logs incorporate typicalfolksonomy properties and that approaches to leverage the inherent semantics of folksonomies can be applied to query logsas well. },
  author = {Benz, Dominik and Hotho, Andreas and Jäschke, Robert and Krause, Beate and Stumme, Gerd},
  interhash = {dae3931a5f445dc67bf111b26f753c36},
  intrahash = {bf96c01262d15fb6eaaf558ecb9a9e69},
  journal = {Datenbank-Spektrum},
  month = jun,
  number = 1,
  pages = {15--24},
  title = {Query Logs as Folksonomies},
  url = {http://dx.doi.org/10.1007/s13222-010-0004-8},
  volume = 10,
  year = 2010
}

@inproceedings{krause2008comparison,
  abstract = {Social bookmarking systems allow users to store links to internet resources on a web page. As social bookmarking systems are growing in popularity, search algorithms have been developed that transfer the idea of link-based rankings in the Web to a social bookmarking system’s
data structure. These rankings differ from traditional search engine rankings in that they incorporate the rating of users. 

In this study, we compare search in social bookmarking systems with traditionalWeb search. In the first part, we compare the user activity and behaviour in both kinds of systems, as well as the overlap of the underlying sets of URLs. In the second part,we compare graph-based and vector space rankings for social bookmarking systems with commercial search engine rankings.

Our experiments are performed on data of the social bookmarking system Del.icio.us and on rankings and log data from Google, MSN, and AOL. We will show that part of the difference between the systems is due to different behaviour (e. g., the concatenation of multi-word lexems
to single terms in Del.icio.us), and that real-world events may trigger similar behaviour in both kinds of systems. We will also show that a graph-based ranking approach on folksonomies yields results that are closer to the rankings of the commercial search engines than vector space
retrieval, and that the correlation is high in particular for the domains that are well covered by the social bookmarking system.},
  address = {Heidelberg},
  author = {Krause, Beate and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Advances in Information Retrieval, 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 = {86dbae2e531c7f68592f5780b46b6a70},
  pages = {101-113},
  publisher = {Springer},
  series = {LNAI},
  title = {A Comparison of Social Bookmarking  with Traditional Search},
  volume = 4956,
  year = 2008
}

@inproceedings{grahl2007clustering,
  abstract = {Currently, social bookmarking systems provide intuitive support for browsing locally their content. A global view is usually presented by the tag cloud of the
system, but it does not allow a conceptual drill-down, e. g., along a conceptual hierarchy. In this paper, we present a clustering approach for computing such a conceptual hierarchy for a given folksonomy. The hierarchy is complemented with ranked lists of users and resources most related to each cluster. The rankings are computed using our FolkRank algorithm. We have evaluated our approach on large scale data from the del.icio.us bookmarking system.},
  address = {Graz, Austria},
  author = {Grahl, Miranda and Hotho, Andreas and Stumme, Gerd},
  booktitle = {7th International Conference on Knowledge Management (I-KNOW '07)},
  interhash = {5cf58d2fdd3c17f0b0c54ce098ff5b60},
  intrahash = {334d3ab11400c4a3ea3ed5b1e95c1855},
  issn = {0948-695x},
  month = sep,
  pages = {356-364},
  publisher = {Know-Center},
  title = {Conceptual Clustering of Social Bookmarking Sites},
  year = 2007
}

@inproceedings{cattuto08-semantic,
  abstract = {Social bookmarking systems allow users to organise collections of resources on the Web in a collaborative fashion. The increasing popularity of these systems as well as first insights into their emergent semantics have made them relevant to disciplines like knowledge extraction and ontology learning. The problem of devising methods to measure the semantic relatedness between tags and characterizing it semantically is still largely open. Here we analyze three measures of tag relatedness: tag co-occurrence, cosine similarity of co-occurrence distributions, and FolkRank, an adaptation of the PageRank algorithm to folksonomies. Each measure is computed on tags from a large-scale dataset crawled from the social bookmarking system del.icio.us. To provide a semantic grounding of our findings, a connection to WordNet (a semantic lexicon for the English language) is established by mapping tags into synonym sets of WordNet, and applying there well-known metrics of semantic similarity. Our results clearly expose different characteristics of the selected measures of relatedness, making them applicable to different subtasks of knowledge extraction such as synonym detection or discovery of concept hierarchies.},
  address = {Patras, Greece},
  author = {Cattuto, Ciro and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Proceedings of the 3rd Workshop on Ontology Learning and Population (OLP3)},
  interhash = {cc62b733f6e0402db966d6dbf1b7711f},
  intrahash = {3b0aca61b24e4343bd80390614e3066e},
  month = {July},
  title = {Semantic Analysis of Tag Similarity Measures in Collaborative Tagging Systems},
  url = {http://olp.dfki.de/olp3/},
  year = 2008
}

@inproceedings{krause2008antisocial,
  author = {Krause, Beate and Schmitz, Christoph and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Proc. of the Fourth International Workshop on  Adversarial Information Retrieval on the Web},
  interhash = {a45d40ac7776551301ad9dde5b25357f},
  intrahash = {6357f535000a383f228f1e8e56ca86ca},
  title = {The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems},
  url = {http://airweb.cse.lehigh.edu/2008/submissions/krause_2008_anti_social_tagger.pdf},
  year = 2008
}

@inproceedings{Jaeschke2008logsonomy,
  abstract = {In social bookmarking systems users describe bookmarks
by keywords called tags. The structure behind
these social systems, called folksonomies, can be
viewed as a tripartite hypergraph of user, tag and resource
nodes. This underlying network shows specific
structural properties that explain its growth and the possibility
of serendipitous exploration.
Search engines filter the vast information of the web.
Queries describe a user’s information need. In response
to the displayed results of the search engine, users click
on the links of the result page as they expect the answer
to be of relevance. The clickdata can be represented as a
folksonomy in which queries are descriptions of clicked
URLs. This poster analyzes the topological characteristics
of the resulting tripartite hypergraph of queries,
users and bookmarks of two query logs and compares it
two 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
}

@article{cattuto2007network,
  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{grahl07conceptualKdml,
  author = {Grahl, Miranda and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Workshop Proceedings of Lernen -- Wissensentdeckung -- Adaptivität (LWA 2007)},
  editor = {Hinneburg, Alexander},
  interhash = {9c3bb05456bf11bcd88a1135de51f7d9},
  intrahash = {6d5188d66564fe4ed7386e28868504de},
  isbn = {978-3-86010-907-6},
  month = sep,
  pages = {50-54},
  publisher = {Martin-Luther-Universität Halle-Wittenberg},
  title = {Conceptual Clustering of Social Bookmark Sites},
  url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2007/kdml_recommender_final.pdf},
  vgwort = {14},
  year = 2007
}

@inproceedings{jaeschke06trias,
  address = {Hong Kong},
  author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd},
  booktitle = {Proceedings of the 6th IEEE International Conference on Data Mining     (ICDM 06)},
  doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2006.162},
  interhash = {b4964c3bdd2991a80873d7080ef6a73e},
  intrahash = {e387c294129e11f4221514d5fa807e26},
  isbn = {0-7695-2701-9},
  issn = {1550-4786},
  month = {December},
  pages = {907-911},
  publisher = {IEEE Computer Society},
  title = {TRIAS - An Algorithm for Mining Iceberg Tri-Lattices},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/jaeschke2006trias.pdf},
  vgwort = {19},
  year = 2006
}