Textual Data Modeling

Textual Data Modeling is a formal methodological framework within digital textual scholarship that specifies the structural, semantic, and syntactic representations of textual entities and their relationships, distinguishing it from general data modeling by its exclusive focus on the interpretive, philological, and computational treatment of textual variants, annotations, and critical editions.

182

Publications

11.8K

Citations

611

Authors

351

Institutions

Publications per year

2017–2026

105

Authors

611

  1. RH
    Renjie He

    National University of Defense Technology, China

    2 publications · 43 citations

    2

    h-index

  2. CL
    Christopher Lucas

    Washington University in St. Louis, United States

    2 publications · 2.4K citations

    2

    h-index

  3. NT
    Nina Tahmasebi

    University of Gothenburg, Sweden

    2 publications · 31 citations

    2

    h-index

  4. ZZ
    Zhongshan Zhang

    National University of Defense Technology, China

    2 publications · 43 citations

    2

    h-index

  5. SZ
    Shuangfei Zhai

    Binghamton University, United States

    2 publications · 111 citations

    2

    h-index

1–5 of 611

Venues

  1. arXiv (Cornell University)

    Repository · 7 publications · 166 citations

    7

    h-index

  2. Expert Systems with Applications

    4 publications · 226 citations

    4

    h-index

  3. SSRN Electronic Journal

    Repository · 3 publications · 76 citations

    3

    h-index

  4. IEEE Access

    3 publications · 104 citations

    3

    h-index

  5. Computers in Industry

    2 publications · 52 citations

    2

    h-index

1–5