@inproceedings{mitzlaff2014summary,
  abstract = {The 15th ECML PKDD Discovery Challenge centered around the recommendation
 of given names. Participants of the challenge implemented algorithms
 that were tested both offline - on data collected by the name search
 engine Nameling - and online within Nameling. Here, we describe both
 tasks in detail and discuss the publicly available datasets. We motivate
 and explain the chosen evaluation of the challenge, and we summarize
 the different approaches applied to the name recommendation tasks.
 Finally, we present the rankings and winners of the offline and the
 online phase.},
  address = {Aachen, Germany},
  author = {Mitzlaff, Folke and Doerfel, Stephan and Hotho, Andreas and Jäschke, Robert and Mueller, Juergen},
  booktitle = {15th Discovery Challenge of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2013, Prague, Czech Republic - Sctober 27, 2013. Proceedings},
  interhash = {6945009ac2fd770a84c47f2a0e192802},
  intrahash = {e279965dffa803ee660e4026fe48340a},
  issn = {1613-0073},
  pages = {7--24},
  publisher = {CEUR-WS},
  title = {Summary of the 15th Discovery Challenge: Recommending Given Names},
  url = {http://ceur-ws.org/Vol-1120/},
  volume = 1120,
  year = 2014
}

@inproceedings{krause2008logsonomy,
  abstract = {Social bookmarking systems constitute an establishedpart of the Web 2.0. In such systemsusers describe bookmarks by keywordscalled tags. The structure behind these socialsystems, called folksonomies, can be viewedas a tripartite hypergraph of user, tag and resourcenodes. This underlying network showsspecific structural properties that explain itsgrowth and the possibility of serendipitousexploration.Today’s search engines represent the gatewayto retrieve information from the World WideWeb. Short queries typically consisting oftwo to three words describe a user’s informationneed. In response to the displayedresults of the search engine, users click onthe links of the result page as they expectthe answer to be of relevance.This clickdata can be represented as a folksonomyin which queries are descriptions ofclicked URLs. The resulting network structure,which we will term logsonomy is verysimilar to the one of folksonomies. In orderto find out about its properties, we analyzethe topological characteristics of the tripartitehypergraph of queries, users and bookmarkson a large snapshot of del.icio.us andon query logs of two large search engines.All of the three datasets show small worldproperties. The tagging behavior of users,which is explained by preferential attachmentof the tags in social bookmark systems, isreflected in the distribution of single querywords in search engines. We can concludethat the clicking behaviour of search engineusers based on the displayed search resultsand the tagging behaviour of social bookmarkingusers is driven by similar dynamics.},
  address = {New York, NY, USA},
  author = {Krause, Beate and Jäschke, Robert and Hotho, Andreas and Stumme, Gerd},
  booktitle = {HT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia},
  doi = {http://doi.acm.org/10.1145/1379092.1379123},
  interhash = {6d34ea1823d95b9dbf37d4db4d125d2a},
  intrahash = {e64d14f3207766f4afc65983fa759ffe},
  isbn = {978-1-59593-985-2},
  location = {Pittsburgh, PA, USA},
  pages = {157--166},
  publisher = {ACM},
  title = {Logsonomy - Social Information Retrieval with Logdata},
  url = {http://portal.acm.org/citation.cfm?id=1379092.1379123&coll=ACM&dl=ACM&type=series&idx=SERIES399&part=series&WantType=Journals&title=Proceedings%20of%20the%20nineteenth%20ACM%20conference%20on%20Hypertext%20and%20hypermedia},
  vgwort = {17},
  year = 2008
}