Uncertainty Representation

Uncertainty Representation is a formal framework within Knowledge Representation that models incomplete, imprecise, or probabilistic information to enable reasoning under conditions of uncertainty.

6.3K

Publications

504.7K

Citations

10.6K

Authors

2.8K

Institutions

Publications per year

2017–2026

1.6K

Authors

10.6K

  1. DD
    Didier Dubois

    Université Toulouse III - Paul Sabatier, France

    105 publications · 12.4K citations

    50

    h-index

  2. HP
    Henri Prade

    Université Toulouse III - Paul Sabatier, France

    76 publications · 10.2K citations

    42

    h-index

  3. RR
    Ronald R. Yager

    Iona College, United States

    87 publications · 4.8K citations

    37

    h-index

  4. YD
    Yong Deng

    University of Electronic Science and Technology of China, China

    52 publications · 3.2K citations

    34

    h-index

  5. JM
    Jerry M. Mendel

    University of Southern California, United States

    37 publications · 6.7K citations

    29

    h-index

1–5 of 10.6K

Venues

  1. IEEE Transactions on Fuzzy Systems

    TFS · 170 publications · 19.9K citations

    65

    h-index

  2. Fuzzy Sets and Systems

    162 publications · 17.1K citations

    53

    h-index

  3. Information Sciences

    142 publications · 38.4K citations

    53

    h-index

  4. International Journal of Intelligent Systems

    137 publications · 9.4K citations

    51

    h-index

  5. arXiv (Cornell University)

    Repository · 174 publications · 12.7K citations

    49

    h-index

1–5