Towards an On-Line Analysis of Tweets Processing

  • Sandra Bringay
  • Nicolas Béchet
  • Flavien Bouillot
  • Pascal Poncelet
  • Mathieu Roche
  • Maguelonne Teisseire
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6861)


Tweets exchanged over the Internet represent an important source of information, even if their characteristics make them difficult to analyze (a maximum of 140 characters, etc.). In this paper, we define a data warehouse model to analyze large volumes of tweets by proposing measures relevant in the context of knowledge discovery. The use of data warehouses as a tool for the storage and analysis of textual documents is not new but current measures are not well-suited to the specificities of the manipulated data. We also propose a new way for extracting the context of a concept in a hierarchy. Experiments carried out on real data underline the relevance of our proposal.


Information Retrieval Data Warehouse Textual Data Probabilistic Latent Semantic Analysis Word Dimension 
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 2011

Authors and Affiliations

  • Sandra Bringay
    • 1
    • 2
  • Nicolas Béchet
    • 3
  • Flavien Bouillot
    • 1
  • Pascal Poncelet
    • 1
  • Mathieu Roche
    • 1
  • Maguelonne Teisseire
    • 1
    • 4
  1. 1.LIRMM – CNRSUniv. Montpellier 2France
  2. 2.Dept MIApUniv. Montpellier 3France
  3. 3.INRIA Rocquencourt - Domaine de VoluceauFrance

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