Entity Encoding

Entity Encoding is a methodological framework within text encoding that systematically represents named entities in natural language texts as structured symbolic forms to preserve their semantic identity and relational context during computational processing.

7

Publications

279

Citations

26

Authors

11

Institutions

Publications per year

2017–2026

3

Authors

26

  1. YW
    Yuzhuo Wang

    University of British Columbia, Canada

    1 publications · 37 citations

    1

    h-index

  2. ZW
    Zhen Wen

    Soochow University, China

    1 publications · 20 citations

    1

    h-index

  3. JH
    Janne Haverinen

    University of Oulu, Finland

    1 publications · 21 citations

    1

    h-index

  4. SS
    Sheng Shen

    University of California, Berkeley, United States

    1 publications · 54 citations

    1

    h-index

  5. KK
    Kevin Knight

    University of Southern California, United States

    1 publications · 20 citations

    1

    h-index

1–5 of 26

Venues

  1. Information Processing & Management

    1 publications · 37 citations

    1

    h-index

  2. eScholarship (California Digital Library)

    Repository · 1 publications · 33 citations

    1

    h-index

  3. Personal and Ubiquitous Computing

    1 publications · 21 citations

    1

    h-index

  4. Journal of Pragmatics

    1 publications · 78 citations

    1

    h-index

1–4