• DocumentCode
    3325617
  • Title

    T-Time: Threshold-Based Data Mining on Time Series

  • Author

    Assfalg, J. ; Kriegel, Hans-Peter ; Kröger, Peer ; Kunath, Peter ; Pryakhin, Alexey ; Renz, Matthias

  • Author_Institution
    Inst. for Inf., Ludwig-Maximilians-Univ. Munchen, Munich
  • fYear
    2008
  • fDate
    7-12 April 2008
  • Firstpage
    1620
  • Lastpage
    1623
  • Abstract
    Mining time series data is an important approach for the analysis in many application areas as diverse as biology, environmental research, medicine, or stock chart analysis. As nearly all data mining tasks on this kind of data depend on a distance function between two time series, a huge number of such functions has been developed during the last decades. The introduction of threshold-based distance functions presented a new concept of time series similarity and these functions were applied to data mining techniques on a wide spectrum of time series data. In this demonstration, we present the Java toolkit T-Time which is able to perform several data mining tasks for a complete range of threshold values in an interactive way. The results are visually presented in a very concise way so that the user can easily identify important threshold values. Combined with domain-specific knowledge, these pivotal values can yield novel insights beyond the means of the underlying data mining techniques the analysis is based on.
  • Keywords
    Java; data mining; time series; Java toolkit T-Time; threshold-based data mining; threshold-based distance function; time series data; Biomedical informatics; Clustering algorithms; Data analysis; Data mining; Euclidean distance; Humans; Inspection; Java; Time series analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering, 2008. ICDE 2008. IEEE 24th International Conference on
  • Conference_Location
    Cancun
  • Print_ISBN
    978-1-4244-1836-7
  • Electronic_ISBN
    978-1-4244-1837-4
  • Type

    conf

  • DOI
    10.1109/ICDE.2008.4497636
  • Filename
    4497636