QuickSearch:   Number of matching entries: 0.

Search Settings

    AuthorTitleYearJournal/ProceedingsReftypeDOI/URL
    Grahl, M., Hotho, A. & Stumme, G. Conceptual Clustering of Social Bookmark Sites

    [BibTeX]

    		 2007 Workshop Proceedings of Lernen -- Wissensentdeckung -- Adaptivität (LWA 2007), pp. 50-54  inproceedings URL 
    BibTeX: 
    @inproceedings{grahl07conceptualKdml,
  author = {Grahl, Miranda and Hotho, Andreas and Stumme, Gerd},
  title = {Conceptual Clustering of Social Bookmark Sites},
  booktitle = {Workshop Proceedings of Lernen -- Wissensentdeckung -- Adaptivität (LWA 2007)},
  publisher = {Martin-Luther-Universität Halle-Wittenberg},
  year = {2007},
  pages = {50-54},
  url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2007/kdml_recommender_final.pdf}
}
    Grahl, M., Hotho, A. & Stumme, G. Conceptual Clustering of Social Bookmark Sites

    [BibTeX]

    		 2007 Workshop Proceedings of Lernen -- Wissensentdeckung -- Adaptivität (LWA 2007), pp. 50-54  inproceedings URL 
    BibTeX: 
    @inproceedings{grahl07conceptualKdml,
  author = {Grahl, Miranda and Hotho, Andreas and Stumme, Gerd},
  title = {Conceptual Clustering of Social Bookmark Sites},
  booktitle = {Workshop Proceedings of Lernen -- Wissensentdeckung -- Adaptivität (LWA 2007)},
  publisher = {Martin-Luther-Universität Halle-Wittenberg},
  year = {2007},
  pages = {50-54},
  url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2007/kdml_recommender_final.pdf}
}
    Grahl, M., Hotho, A. & Stumme, G. Conceptual Clustering of Social Bookmarking Sites

    [Abstract] [BibTeX]

    		 2007 7th International Conference on Knowledge Management (I-KNOW '07), pp. 356-364  inproceedings  
    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.
    BibTeX: 
    @inproceedings{grahl2007clustering,
  author = {Grahl, Miranda and Hotho, Andreas and Stumme, Gerd},
  title = {Conceptual Clustering of Social Bookmarking Sites},
  booktitle = {7th International Conference on Knowledge Management (I-KNOW '07)},
  publisher = {Know-Center},
  year = {2007},
  pages = {356-364}
}

    Created by JabRef on 27/04/2024.