Corpus ID: 3352788

Mining Sub-Interval Relationships In Time Series Data

  title={Mining Sub-Interval Relationships In Time Series Data},
  author={Saurabh Agrawal and Saurabh Verma and G. Atluri and A. Karpatne and S. Liess and A. MacDonald and Snigdhansu Chatterjee and Vipin Kumar},
Time-series data is being increasingly collected and stud- ied in several areas such as neuroscience, climate science, transportation, and social media. Discovery of complex patterns of relationships between individual time-series, using data-driven approaches can improve our understanding of real-world systems. While traditional approaches typically study relationships between two entire time series, many interesting relationships in real-world applications exist in small sub-intervals of time… Expand


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  • T. Liao
  • Computer Science
  • Pattern Recognit.
  • 2005
This paper surveys and summarizes previous works that investigated the clustering of time series data in various application domains, including general-purpose clustering algorithms commonly used in time series clustering studies. Expand
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The problem of indexing time series has attracted much interest. Most algorithms used to index time series utilize the Euclidean distance or some variation thereof. However, it has been forcefullyExpand