An Examination of Multivariate Time Series Hashing with Applications to Health Care

@article{Kale2014AnEO,
  title={An Examination of Multivariate Time Series Hashing with Applications to Health Care},
  author={David C. Kale and Dian Gong and Zhengping Che and Yan Liu and G{\'e}rard G. Medioni and Randall C. Wetzel and Patrick Ross},
  journal={2014 IEEE International Conference on Data Mining},
  year={2014},
  pages={260-269}
}
As large-scale multivariate time series data become increasingly common in application domains, such as health care and traffic analysis, researchers are challenged to build efficient tools to analyze it and provide useful insights. Similarity search, as a basic operator for many machine learning and data mining algorithms, has been extensively studied before, leading to several efficient solutions. However, similarity search for multivariate time series data is intrinsically challenging… CONTINUE READING

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