Graph-based Document Representation

Graph-Based Document Representation is a document representation paradigm that models documents as graph structures, where nodes represent linguistic or semantic units (e.g., terms, sentences, or concepts) and edges encode syntactic, semantic, or discourse-level relationships among them, distinguishing it from sequential or vector-space representations by explicitly capturing non-linear structural dependencies within and across documents.

191

Publications

7.8K

Citations

575

Authors

241

Institutions

Publications per year

2017–2026

84

Authors

575

  1. JL
    Josep Lladós

    Universitat Autònoma de Barcelona, Spain

    7 publications · 255 citations

    7

    h-index

  2. AK
    Abraham Kandel

    University of South Florida, United States

    4 publications · 186 citations

    4

    h-index

  3. DV
    Darnes Vilariño

    Benemérita Universidad Autónoma de Puebla, Mexico

    4 publications · 92 citations

    4

    h-index

  4. FD
    Fragkiskos D. Malliaros

    CentraleSupélec, France

    4 publications · 179 citations

    4

    h-index

  5. HB
    Horst Bunke

    University of Bern, Switzerland

    4 publications · 353 citations

    4

    h-index

1–5 of 575

Venues

  1. arXiv (Cornell University)

    Repository · 8 publications · 389 citations

    8

    h-index

  2. Neurocomputing

    3 publications · 130 citations

    3

    h-index

  3. 3

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 91 citations

    3

    h-index

  5. Information Processing & Management

    3 publications · 100 citations

    3

    h-index

1–5