On Deriving Tagsonomies: Keyword Relations Coming from Crowd

  • Michal Barla
  • Mária Bieliková
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5796)


Many keyword-based approaches to text classification, information retrieval or even user modeling for adaptive web-based system could benefit from knowledge on relations between various keywords, which gives further possibilities to compare them, evaluate their distance etc. This paper proposes an approach how to determine keyword relations (mainly a parent-child relationship) by leveraging collective wisdom of the masses, present in data of collaborative (social) tagging systems on the Web. The feasibility of our approach is demonstrated on the data coming from the social bookmarking systems delicious and CiteULike.


Bipartite Graph User Model Spreading Activation Implicit Feedback Social Bookmark System 
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 2009

Authors and Affiliations

  • Michal Barla
    • 1
  • Mária Bieliková
    • 1
  1. 1.Institute of Informatics and Software Engineering, Faculty of Informatics and Information TechnologiesSlovak University of TechnologyBratislavaSlovakia

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