%0 
%0 Conference Proceedings
%A Mitzlaff, Folke & Stumme, Gerd
%D 2012
%T Ranking Given Names
%E Marathe, Madhav & Contractor, Noshir
%B Proceedings of the 1st ASE International Conference on Social Informatics
%C 
%I IEEE computer society
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%6
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%P 185-191
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%F mitzlaff2012ranking
%K 2012, analysis, engine, given, itegpub, l3s, myown, names, ranking, serach
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%0 Conference Proceedings
%A Jäschke, Robert; Marinho, Leandro Balby; Hotho, Andreas; Schmidt-Thieme, Lars & Stumme, Gerd
%D 2007
%T Tag Recommendations in Folksonomies
%E Kok, Joost N.; Koronacki, Jacek; de Mántaras, Ramon López; Matwin, Stan; Mladenic, Dunja & Skowron, Andrzej
%B Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases
%C Berlin, Heidelberg
%I Springer
%V 4702
%6
%N 
%P 506-514
%& 
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%S Lecture Notes in Computer Science
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%@ 978-3-540-74975-2
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%F jaeschke2007tag
%K 2007, FolkRank, Folksonomies, Recommendations, folksonomies, itegpub, l3s, myown, nepomuk, ranking, recommendations, tagging
%X 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.
%Z 
%U http://dx.doi.org/10.1007/978-3-540-74976-9_52
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%A Hotho, Andreas; Jäschke, Robert; Schmitz, Christoph & Stumme, Gerd
%D 2006
%T FolkRank: A Ranking Algorithm for Folksonomies
%E 
%B Proc. FGIR 2006
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%F hotho2006folkrank
%K 2006, algorithm, folkrank, ir, itegpub, l3s, myown, nepomuk, pagerank, ranking
%X  In social bookmark tools users are setting up
lightweight conceptual structures called folksonomies. Currently,
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 find communities within the
folksonomy and is used to structure search results. All findings are
demonstrated on a large scale dataset. A long version of this paper
has been published at the European Semantic Web Conference
2006.
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%U http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006folkrank.pdf
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%A Hotho, Andreas; J\"a,schke, Robert; Schmitz, Christoph & Stumme, Gerd
%D 2006
%T Information Retrieval in Folksonomies: Search and Ranking
%E 
%B Proceedings of the 3rd European Semantic Web Conference
%C 
%I Springer
%V 
%6
%N 
%P 411-426
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%S Lecture Notes in Computer Science
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%F hotho2006information
%K FCA, OntologyHandbook, folkrank, folksonomy, graph, information, mining, pagerank, rank, ranking, retrieval, search, seminar2006
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%A Hotho, Andreas; Jäschke, Robert; Schmitz, Christoph & Stumme, Gerd
%D 2006
%T Information Retrieval in Folksonomies: Search and Ranking
%E Sure, York & Domingue, John
%B The Semantic Web: Research and Applications
%C Heidelberg
%I Springer
%V 4011
%6
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%P 411-426
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%S LNAI
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%8 June
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%K 2006, FCA, IR, OntologyHandbook, folkrank, folksonomy, information, informationretrieval, itegpub, mimose, myown, pagerank, ranking, retrieval
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%0 
%0 Conference Proceedings
%A Hotho, Andreas; J�schke, Robert; Schmitz, Christoph & Stumme, Gerd
%D 2006
%T Information Retrieval in Folksonomies: Search and Ranking
%E Sure, York & Domingue, John
%B The Semantic Web: Research and Applications
%C Heidelberg
%I Springer
%V 4011
%6
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%P 411-426
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%S LNAI
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%K 2006, FCA, IR, OntologyHandbook, folkrank, folksonomy, information, informationretrieval, itegpub, mimose, myown, pagerank, ranking, retrieval
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