Improving the Clustering of Blogosphere with a Self-term Enriching Technique

  • Fernando Perez-Tellez
  • David Pinto
  • John Cardiff
  • Paolo Rosso
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5729)


The analysis of blogs is emerging as an exciting new area in the text processing field which attempts to harness and exploit the vast quantity of information being published by individuals. However, their particular characteristics (shortness, vocabulary size and nature, etc.) make it difficult to achieve good results using automated clustering techniques. Moreover, the fact that many blogs may be considered to be narrow domain means that exploiting external linguistic resources can have limited value. In this paper, we present a methodology to improve the performance of clustering techniques on blogs, which does not rely on external resources. Our results show that this technique can produce significant improvements in the quality of clusters produced.


Cluster Algorithm Term Expansion Cluster Task Pointwise Mutual Information Narrow Domain 
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

  • Fernando Perez-Tellez
    • 1
  • David Pinto
    • 2
  • John Cardiff
    • 1
  • Paolo Rosso
    • 3
  1. 1.Institute of Technology TallaghtSocial Media Research GroupDublinIreland
  2. 2.Benemerita Universidad Autónoma de PueblaMexico
  3. 3.Natural Language Engineering Lab. - EliRF, Dept. Sistemas Informáticos y ComputaciónUniversidad PolitécnicaValenciaSpain

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