Search (3 results, page 1 of 1)

  • × theme_ss:"Metadaten"
  • × theme_ss:"Social tagging"
  1. Social tagging in a linked data environment. Edited by Diane Rasmussen Pennington and Louise F. Spiteri. London, UK: Facet Publishing, 2018. 240 pp. £74.95 (paperback). (ISBN 9781783303380) (2019) 0.00
    0.0033256328 = product of:
      0.013302531 = sum of:
        0.013302531 = weight(_text_:information in 101) [ClassicSimilarity], result of:
          0.013302531 = score(doc=101,freq=10.0), product of:
            0.06134496 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.034944877 = queryNorm
            0.21684799 = fieldWeight in 101, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0390625 = fieldNorm(doc=101)
      0.25 = coord(1/4)
    
    Abstract
    Social tagging, hashtags, and geotags are used across a variety of platforms (Twitter, Facebook, Tumblr, WordPress, Instagram) in different countries and cultures. This book, representing researchers and practitioners across different information professions, explores how social tags can link content across a variety of environments. Most studies of social tagging have tended to focus on applications like library catalogs, blogs, and social bookmarking sites. This book, in setting out a theoretical background and the use of a series of case studies, explores the role of hashtags as a form of linked data?without the complex implementation of RDF and other Semantic Web technologies.
    LCSH
    Libraries and museums / Electronic information resources
    Electronic information resources
    Subject
    Libraries and museums / Electronic information resources
    Electronic information resources
  2. Catarino, M.E.; Baptista, A.A.: Relating folksonomies with Dublin Core (2008) 0.00
    0.0014872681 = product of:
      0.0059490725 = sum of:
        0.0059490725 = weight(_text_:information in 2652) [ClassicSimilarity], result of:
          0.0059490725 = score(doc=2652,freq=2.0), product of:
            0.06134496 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.034944877 = queryNorm
            0.09697737 = fieldWeight in 2652, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2652)
      0.25 = coord(1/4)
    
    Abstract
    Folksonomy is the result of describing Web resources with tags created by Web users. Although it has become a popular application for the description of resources, in general terms Folksonomies are not being conveniently integrated in metadata. However, if the appropriate metadata elements are identified, then further work may be conducted to automatically assign tags to these elements (RDF properties) and use them in Semantic Web applications. This article presents research carried out to continue the project Kinds of Tags, which intends to identify elements required for metadata originating from folksonomies and to propose an application profile for DC Social Tagging. The work provides information that may be used by software applications to assign tags to metadata elements and, therefore, means for tags to be conveniently gathered by metadata interoperability tools. Despite the unquestionably high value of DC and the significance of the already existing properties in DC Terms, the pilot study show revealed a significant number of tags for which no corresponding properties yet existed. A need for new properties, such as Action, Depth, Rate, and Utility was determined. Those potential new properties will have to be validated in a later stage by the DC Social Tagging Community.
  3. Syn, S.Y.; Spring, M.B.: Finding subject terms for classificatory metadata from user-generated social tags (2013) 0.00
    0.0014872681 = product of:
      0.0059490725 = sum of:
        0.0059490725 = weight(_text_:information in 745) [ClassicSimilarity], result of:
          0.0059490725 = score(doc=745,freq=2.0), product of:
            0.06134496 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.034944877 = queryNorm
            0.09697737 = fieldWeight in 745, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0390625 = fieldNorm(doc=745)
      0.25 = coord(1/4)
    
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.5, S.964-980