Event Embedding

Event Embedding is a computational representation method that encodes the semantic and temporal characteristics of events into fixed-dimensional vector spaces to facilitate machine learning tasks involving event understanding and reasoning.

58

Publications

3K

Citations

227

Authors

98

Institutions

Publications per year

2017–2026

42

Authors

227

  1. AM
    Ashutosh Modi

    Saarland University, Germany

    3 publications · 101 citations

    3

    h-index

  2. DG
    Dan Goldwasser

    Purdue University West Lafayette, United States

    3 publications · 89 citations

    3

    h-index

  3. IL
    I‐Te Lee

    Taichung Veterans General Hospital, Taiwan

    3 publications · 89 citations

    3

    h-index

  4. JH
    Jiawei Han

    University of Illinois Urbana-Champaign, United States

    2 publications · 153 citations

    2

    h-index

  5. MG
    Mark Granroth-Wilding

    University of Helsinki, Finland

    2 publications · 268 citations

    2

    h-index

1–5 of 227

Venues

  1. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 2 publications · 184 citations

    2

    h-index

  2. ORBi (University of Liège)

    Repository · 1 publications · 162 citations

    1

    h-index

  3. Journal of High Energy Physics

    JHEP · 1 publications · 118 citations

    1

    h-index

  4. Apollo (University of Cambridge)

    Repository · 1 publications · 113 citations

    1

    h-index

  5. International Conference on Computational Linguistics

    Conference · 1 publications · 96 citations

    1

    h-index

1–5