Search (5 results, page 1 of 1)

  • × theme_ss:"Folksonomies"
  • × theme_ss:"Social tagging"
  • × type_ss:"a"
  1. Catarino, M.E.; Baptista, A.A.: Relating folksonomies with Dublin Core (2008) 0.01 
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    Pages
    S.14-22
    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  2. Peters, I.; Schumann, L.; Terliesner, J.: Folksonomy-basiertes Information Retrieval unter der Lupe (2012) 0.01 
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    Content
    Vgl.: http://www.degruyter.com/view/j/iwp.2012.63.issue-4/iwp-2012-0047/iwp-2012-0047.xml?format=INT.
    Source
    Information - Wissenschaft und Praxis. 63(2012) H.4, S.273-280
  3. Kim, H.L.; Scerri, S.; Breslin, J.G.; Decker, S.; Kim, H.G.: ¬The state of the art in tag ontologies : a semantic model for tagging and folksonomies (2008) 0.01 
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    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  4. Munk, T.B.; Moerk, K.: Folksonomies, tagging communities, and tagging strategies : an empirical study (2007) 0.01 
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    Abstract
    The subject of this article is folksonomies on the Internet. One of the largest folksonomies on the Internet in terms of number of users and tagged websites is the computer program del.icio.us, where more than 100,000 people have tagged the websites that they and others find using their own keywords. How this is done in practice and the patterns to be found are the focus of this article. The empirical basis is the collection of 76,601 different keywords with a total frequency of 178,215 from 500 randomly chosen taggers on del.icio.us at the end of 2005. The keywords collected were then analyzed quantitatively statistically by uncovering their frequency and percentage distribution and through a statistical correspondence analysis in order to uncover possible patterns in the users' tags. Subsequently, a qualitative textual analysis of the tags was made in order to find out by analysis which tagging strategies are represented in the data material. This led to four conclusions. 1) the distribution of keywords follows classic power law; 2) distinct tagging communities are identifiable; 3) the most frequently used tags are situated on a general-specific axis; and 4) nine distinct tagging strategies are observed. These four conclusions are put into perspective collectively in respect of a number of more general and theoretical considerations concerning folksonomies and the classification systems of the future.
  5. Chopin, K.: Finding communities : alternative viewpoints through weblogs and tagging (2008) 0.01 
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    Source
    Journal of documentation. 64(2008) no.4, S.552-575

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