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A Hybrid Approach to Constructing Tag Hierarchies

  • Geir Solskinnsbakk
  • Jon Atle Gulla
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6427)

Abstract

Folksonomies are becoming increasingly popular. They contain large amounts of data which can be mined and utilized for many tasks like visualization, browsing, information retrieval etc. An inherent problem of folksonomies is the lack of structure. In this paper we present an unsupervised approach for generating such structure based on a combination of association rule mining and the underlying tagged material. Using the underlying tagged material we generate a semantic representation of each tag. The semantic representation of the tags is an integral component of the structure generated. The experiment presented in this paper shows promising results with tag structures that correspond well with human judgment.

Keywords

Association Rule Semantic Representation Cosine Similarity Association Rule Mining Textual Content 
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 2010

Authors and Affiliations

  • Geir Solskinnsbakk
    • 1
  • Jon Atle Gulla
    • 1
  1. 1.Department of Computer and Information ScienceNorwegian University of Science and TechnologyTrondheimNorway

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