Interval-based Time Models

Interval-Based Time Models is a temporal knowledge representation framework that formally treats time as a set of durative intervals rather than instantaneous points, enabling the qualitative and relational modeling of temporal events and their logical dependencies over extended periods.

133

Publications

7.3K

Citations

297

Authors

152

Institutions

Publications per year

2017–2026

15

Authors

297

  1. YS
    Yuval Shaḥar

    Ben-Gurion University of the Negev, Israel

    5 publications · 444 citations

    5

    h-index

  2. JM
    Jixin Ma

    University of Greenwich, United Kingdom

    5 publications · 96 citations

    5

    h-index

  3. JF
    James F. Allen

    University of Rochester, United States

    4 publications · 1.2K citations

    4

    h-index

  4. MA
    Mark A. Musen

    Stanford University, United States

    3 publications · 350 citations

    3

    h-index

  5. MG
    Michael G. Kahn

    University of Colorado Denver, United States

    3 publications · 95 citations

    3

    h-index

1–5 of 297

Venues

  1. PubMed

    Repository · 4 publications · 61 citations

    4

    h-index

  2. The Computer Journal

    4 publications · 129 citations

    4

    h-index

  3. International Joint Conference on Artificial Intelligence

    Conference · 3 publications · 303 citations

    3

    h-index

  4. Computational Intelligence

    3 publications · 228 citations

    3

    h-index

  5. Methods of Information in Medicine

    3 publications · 132 citations

    3

    h-index

1–5