Time Series Compression

Time Series Compression is a data reduction technique that belongs to the class of time-series preprocessing methods, specifically distinguished by its purpose of reducing the temporal or amplitude resolution of a time series while preserving essential patterns, trends, and critical features for subsequent analysis or visualization.

166

Publications

15K

Citations

483

Authors

224

Institutions

Publications per year

2017–2026

67

Authors

483

  1. EF
    Eugene Fink

    Carnegie Mellon University, United States

    4 publications · 237 citations

    4

    h-index

  2. HS
    Harith Suman Gandhi

    Carnegie Mellon University, United States

    3 publications · 90 citations

    3

    h-index

  3. CR
    Chris Roadknight

    BT Research, United Kingdom

    2 publications · 25 citations

    2

    h-index

  4. ZW
    Zhaohua Wu

    Florida State University, United States

    2 publications · 63 citations

    2

    h-index

  5. DL
    Daoyuan Li

    University of Luxembourg, Luxembourg

    2 publications · 40 citations

    2

    h-index

1–5 of 483

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 6 publications · 214 citations

    6

    h-index

  2. The Journal of the Acoustical Society of America

    JASA · 3 publications · 68 citations

    3

    h-index

  3. IEEE Access

    2 publications · 45 citations

    3

    h-index

  4. IET Intelligent Transport Systems

    2 publications · 26 citations

    2

    h-index

  5. IEEE Transactions on Information Theory

    2 publications · 26 citations

    2

    h-index

1–5