• DocumentCode
    2892922
  • Title

    Tagging Resources, Tagging Communities

  • Author

    Abrouk, Lylia ; Gross-Amblard, David ; Cullot, Nadine ; Thion-Goasdou, Virginie

  • Author_Institution
    LE2I, Bourgogne Univ., Dijon, France
  • fYear
    2010
  • fDate
    12-14 April 2010
  • Firstpage
    1253
  • Lastpage
    1254
  • Abstract
    Most of the existing social network systems require from their users an explicit statement of their friendship relations. In this paper we focus on implicit communities of Web users and present an approach to automatically detect such communities based on user´s resource manipulations. This approach is dynamic as user groups appear and evolve along with users interests over time. Moreover, new resources are dynamically labeled according to who is manipulating them. Our proposal relies on the fuzzy K-mean clustering method and is assessed on large movie data sets.
  • Keywords
    Internet; fuzzy set theory; information retrieval; pattern clustering; social networking (online); Web users; fuzzy K-mean clustering method; social network systems; tagging communities; tagging resources; Classification algorithms; Clustering algorithms; Clustering methods; Fuzzy sets; Information technology; Motion pictures; Proposals; Social network services; Tagging; Voting; Clustering; Data sharing; Information networks; User distance; Web community;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology: New Generations (ITNG), 2010 Seventh International Conference on
  • Conference_Location
    Las Vegas, NV
  • Print_ISBN
    978-1-4244-6270-4
  • Type

    conf

  • DOI
    10.1109/ITNG.2010.206
  • Filename
    5501556