Commonsense Knowledge Graphs

Commonsense Knowledge Graphs is a structured representation of everyday human knowledge organized as a graph, where nodes denote concepts or entities and edges represent commonsense relationships, enabling machines to reason about typical, implicit, and context-dependent facts not explicitly stated in text.

124

Publications

7.2K

Citations

431

Authors

114

Institutions

Publications per year

2017–2026

113

Variants

Commonsense Knowledge Graph

Authors

431

  1. YC
    Yejin Choi

    University of Washington, United States

    12 publications · 1.6K citations

    12

    h-index

  2. AB
    Antoine Bosselut

    University of Washington, United States

    12 publications · 1.6K citations

    11

    h-index

  3. CB
    Chandra Bhagavatula

    University of Washington, United States

    6 publications · 554 citations

    6

    h-index

  4. RL
    Ronan Le Bras

    University of Washington, United States

    6 publications · 520 citations

    6

    h-index

  5. CM
    Chaitanya Malaviya

    Allen Institute for Artificial Intelligence, United States

    5 publications · 1.1K citations

    5

    h-index

1–5 of 431

Venues

  1. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 14 publications · 629 citations

    13

    h-index

  2. arXiv (Cornell University)

    Repository · 22 publications · 515 citations

    13

    h-index

  3. 4

    h-index

  4. Expert Systems with Applications

    2 publications · 58 citations

    2

    h-index

  5. IEEE Intelligent Systems

    2 publications · 109 citations

    2

    h-index

1–5