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Journal of Intelligent Information Systems

, Volume 38, Issue 3, pp 685–708 | Cite as

In & out zooming on time-aware user/tag clusters

  • Eirini Giannakidou
  • Vassiliki Koutsonikola
  • Athena Vakali
  • Ioannis Kompatsiaris
Article

Abstract

The common ground behind most approaches that analyze social tagging systems is addressing the information challenge that emerges from the massive activity of millions of users who interact and share resources and/or metadata online. However, lack of any time-related data in the analysis process implicitly denies much of the dynamic nature of social tagging activity. In this paper we claim that holding a temporal dimension, allows for tracking macroscopic and microscopic users’ interests, detecting emerging trends and recognizing events. To this end, we propose a time-aware co-clustering approach for acquiring semantic and temporal patterns out of the tagging activity. The resulted clusters contain both users and tags of similar patterns over time, and reveal non-obvious or “hidden” relations among users and topics of their common interest. Zoom in & out views serve as visualization methods on different aspects of the clusters’ structure, in order to evaluate the efficiency of the approach.

Keywords

Time-aware clustering Social tagging systems Users’ interests over time Events 

Notes

Acknowledgements

This work was supported by the FP7 project WeKnowIt, partially funded by the EC under contract number 215453.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Eirini Giannakidou
    • 1
  • Vassiliki Koutsonikola
    • 1
  • Athena Vakali
    • 1
  • Ioannis Kompatsiaris
    • 2
  1. 1.Department of InformaticsAristotle UniversityThessalonikiGreece
  2. 2.Informatics and Telematics Institute, CERTHThermi-ThessalonikiGreece

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