Mining Time Series with Mine Time

  • Lefteris Koumakis
  • Vassilis Moustakis
  • Alexandros Kanterakis
  • George Potamias
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3955)


We present, Mine Time, a tool that supports discovery over time series data. Mine Time is realized by the introduction of novel algorithmic processes, which support assessment of coherence and similarity across timeseries data. The innovation comes from the inclusion of specific ‘control’ operations in the elaborated time-series matching metric. The final outcome is the clustering of time-series into similar-groups. Clustering is performed via the appropriate customization of a phylogeny-based clustering algorithm and tool. We demonstrate Mine Time via two experiments.


Mine Time Dynamic Time Warping Neighbor Join Phylogenetic Cluster Star Tree 
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 2006

Authors and Affiliations

  • Lefteris Koumakis
    • 1
  • Vassilis Moustakis
    • 1
    • 2
  • Alexandros Kanterakis
    • 1
  • George Potamias
    • 1
  1. 1.Institute of Computer ScienceFoundation for Research and Technology-Hellas (FORTH)Heraklion, CreteGreece
  2. 2.Department of Production and Management EngineeringTechnical University of CreteKounoupidiana, Chania, CreteGreece

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