Semantic Compression

Semantic Compression is a data abstraction technique that reduces the size of data representations by eliminating redundant or extraneous semantic information while preserving essential meaning, distinguishing it from syntactic compression methods through its focus on high-level conceptual fidelity.

73

Publications

2.9K

Citations

266

Authors

118

Institutions

Publications per year

2017–2026

37

Authors

266

  1. HZ
    Haijun Zhang

    University of Science and Technology Beijing, China

    2 publications · 188 citations

    2

    h-index

  2. SV
    Svetha Venkatesh

    Deakin University, Australia

    2 publications · 21 citations

    2

    h-index

  3. JD
    Javier D. Fernández

    Universidad de Valladolid, Spain

    2 publications · 57 citations

    2

    h-index

  4. SG
    Stewart Greenhill

    Curtin University, Australia

    2 publications · 21 citations

    2

    h-index

  5. FS
    Floriano Scioscia

    Polytechnic University of Bari, Italy

    2 publications · 99 citations

    2

    h-index

1–5 of 266

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 52 citations

    2

    h-index

  2. Journal of Spatial Information Science

    JOSIS · 2 publications · 100 citations

    2

    h-index

  3. IEEE Wireless Communications

    2 publications · 124 citations

    2

    h-index

  4. Knowledge-Based Systems

    2 publications · 81 citations

    2

    h-index

  5. IEEE Wireless Communications Letters

    1 publications · 30 citations

    1

    h-index

1–5