Correlated Trends: A New Representation for Imperfect and Large Dataseries

  • Miguel Delgado
  • Waldo Fajardo
  • Miguel Molina-Solana
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8132)


The computational representation of dataseries is a task of growing interest in our days. However, as these data are often imperfect, new representation models are required to effectively handle them. This work presents Frequent Correlated Trends, our proposal for representing uncertain and imprecise multivariate dataseries. Such a model can be applied to any domain where dataseries contain patterns that recur in similar —but not identical— shape. We describe here the model representation and an associated learning algorithm.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Miguel Delgado
    • 1
  • Waldo Fajardo
    • 1
  • Miguel Molina-Solana
    • 1
  1. 1.Department Computer Science and Artificial IntelligenceUniversidad de GranadaGranadaSpain

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