Uncertainty Reduction Techniques

Uncertainty Reduction Techniques is a systematic methodological framework designed to identify, quantify, and mitigate representational and analytical ambiguities in network visualizations through targeted algorithmic or visual adaptations that enhance data fidelity and user interpretability.

285

Publications

16.9K

Citations

812

Authors

428

Institutions

Publications per year

2017–2026

88

Authors

812

  1. WB
    William B. Gudykunst

    Arizona State University, United States

    6 publications · 354 citations

    6

    h-index

  2. DJ
    Denis José Schiozer

    Universidade Estadual de Campinas (UNICAMP), Brazil

    4 publications · 53 citations

    4

    h-index

  3. DG
    Debasish Ghose

    Indian Institute of Science Bangalore, India

    4 publications · 86 citations

    4

    h-index

  4. PB
    P. B. Sujit

    Universidade do Porto, Portugal

    4 publications · 86 citations

    4

    h-index

  5. PM
    Patti M. Valkenburg

    University of Amsterdam, Netherlands

    3 publications · 439 citations

    3

    h-index

1–5 of 812

Venues

  1. Journal of Mechanical Design

    5 publications · 100 citations

    5

    h-index

  2. 4

    h-index

  3. Structural and Multidisciplinary Optimization

    3 publications · 101 citations

    3

    h-index

  4. Communication Research

    CR · 3 publications · 562 citations

    3

    h-index

  5. Journal of Hydrology

    3 publications · 162 citations

    3

    h-index

1–5