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Methodologies for Improved Tag Cloud Generation with Clustering

  • Martin Leginus
  • Peter Dolog
  • Ricardo Lage
  • Frederico Durao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7387)

Abstract

Tag clouds are useful means for navigation in the social web systems. Usually the systems implement the tag cloud generation based on tag popularity which is not always the best method. In this paper we propose methodologies on how to combine clustering into the tag cloud generation to improve coverage and overlap. We study several clustering algorithms to generate tag clouds. We show that by extending cloud generation based on tag popularity with clustering we slightly improve coverage. We also show that if the cloud is generated by clustering independently of the tag popularity baseline we minimize overlap and increase coverage. In the first case we therefore provide more items for a user to explore. In the second case we provide more diverse items for a user to explore. We experiment with the methodologies on two different datasets: Delicious and Bibsonomy. The methodologies perform slightly better on bibsonomy due to its specific focus. The best performing is the hierarchical clustering.

Keywords

Cluster Technique Cloud Generation Complete Linkage Hierarchical Cluster Chained Coverage Agglomerative Hierarchical Cluster Technique 
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 2012

Authors and Affiliations

  • Martin Leginus
    • 1
  • Peter Dolog
    • 1
  • Ricardo Lage
    • 1
  • Frederico Durao
    • 1
  1. 1.Department of Computer ScienceAalborg UniversityDenmark

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