Progressive Filtering

Progressive Filtering is a method in interactive filtering systems that iteratively refines data subsets by successively applying user-informed criteria to enhance retrieval precision while preserving relevant items across dynamic user feedback loops.

31

Publications

1.1K

Citations

73

Authors

35

Institutions

Publications per year

2017–2026

12

Authors

73

  1. UD
    Uwe D. Hanebeck

    Karlsruhe Institute of Technology, Germany

    4 publications · 99 citations

    4

    h-index

  2. AS
    Andreas Savakis

    Rochester Institute of Technology, United States

    3 publications · 74 citations

    3

    h-index

  3. BA
    Bruno Artacho

    Rochester Institute of Technology, United States

    3 publications · 74 citations

    3

    h-index

  4. JS
    Jannik Steinbring

    Karlsruhe Institute of Technology, Germany

    2 publications · 50 citations

    2

    h-index

  5. GA
    Giuliano Armano

    University of Cagliari, Italy

    2 publications · 25 citations

    2

    h-index

1–5 of 73

Venues

  1. Repository KITopen (Karlsruhe Institute of Technology)

    Repository · 2 publications · 50 citations

    2

    h-index

  2. IEEE Transactions on Automatic Control

    1 publications · 19 citations

    1

    h-index

  3. arXiv (Cornell University)

    Repository · 1 publications · 31 citations

    1

    h-index

  4. Numerical Heat Transfer Part A Applications

    1 publications · 53 citations

    1

    h-index

  5. IEEE Transactions on Computers

    1 publications · 25 citations

    1

    h-index

1–5