Temporal Feature Design

Temporal Feature Design is a domain-specific feature engineering methodology that distinguishes itself by explicitly modeling time-dependent patterns and sequential dynamics inherent in temporal data to enhance predictive performance in time-aware machine learning tasks.

23

Publications

682

Citations

84

Authors

47

Institutions

Publications per year

2017–2026

10

Authors

84

  1. CL
    Chengjun Liu

    Chongqing Medical University, China

    1 publications · 11 citations

    1

    h-index

  2. HS
    Hang Shi

    New Jersey Institute of Technology, United States

    1 publications · 11 citations

    1

    h-index

  3. CL
    Chenyang Liu

    Tsinghua University, China

    1 publications · 13 citations

    1

    h-index

  4. SB
    Steven Bethard

    University of Arizona, United States

    1 publications · 75 citations

    1

    h-index

  5. KB
    Ksenia Balabaeva

    ITMO University, Russia

    1 publications · 27 citations

    1

    h-index

1–5 of 84

Venues

  1. Neurocomputing

    1 publications · 28 citations

    1

    h-index

  2. International Journal of Crowd Science

    1 publications · 29 citations

    1

    h-index

  3. Knowledge-Based Systems

    1 publications · 40 citations

    1

    h-index

  4. International Journal of Vehicular Technology

    1 publications · 14 citations

    1

    h-index

  5. ArXiv.org

    Repository · 1 publications · 15 citations

    1

    h-index

1–5