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Symbol Extraction Method and Symbolic Distance for Analysing Medical Time Series

  • Fernando Alonso
  • Loïc Martínez
  • Aurora Pérez
  • Agustín Santamaría
  • Juan Pedro Valente
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4345)

Abstract

The analysis of time series databases is very important in the area of medicine. Most of the approaches that address this problem are based on numerical algorithms that calculate distances, clusters, index trees, etc. However, a symbolic rather than numerical analysis is sometimes needed to search for the characteristics of the time series. Symbolic information helps users to efficiently analyse and compare time series in the same or in a similar way as a domain expert would. This paper focuses on the process of transforming numerical time series into a symbolic domain and on the definition of both this domain and a distance for comparing symbolic temporal sequences. The work is applied to the isokinetics domain within an application called I4.

Keywords

Time series characterization isokinetics symbolic distance information extraction and text mining 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Fernando Alonso
    • 1
  • Loïc Martínez
    • 1
  • Aurora Pérez
    • 1
  • Agustín Santamaría
    • 1
  • Juan Pedro Valente
    • 1
  1. 1.Facultad de InformáticaUniversidad Politécnica de MadridBoadilla del Monte. MadridSpain

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