Mutual Contextualization in Tripartite Graphs of Folksonomies

  • Ching-man Au Yeung
  • Nicholas Gibbins
  • Nigel Shadbolt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4825)


The use of tags to describe Web resources in a collaborative manner has experienced rising popularity among Web users in recent years. The product of such activity is given the name folksonomy, which can be considered as a scheme of organizing information in the users’ own way. This research work attempts to analyze tripartite graphs – graphs involving users, tags and resources – of folksonomies and discuss how these elements acquire their semantics through their associations with other elements, a process we call mutual contextualization. By studying such process, we try to identify solutions to problems such as tag disambiguation, retrieving documents of similar topics and discovering communities of users. This paper describes the basis of the research work, mentions work done so far and outlines future plans.


Bipartite Graph Single User Tripartite Graph Social Annotation Mutual Contextualization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Ching-man Au Yeung
    • 1
  • Nicholas Gibbins
    • 1
  • Nigel Shadbolt
    • 1
  1. 1.Intelligence, Agents and Multimedia Group (IAM), School of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJUK

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