Interactive Data Reduction
Interactive Data Reduction is a methodological framework within interactive filtering that enables users to iteratively refine large datasets through real-time feedback loops, distinguishing itself by integrating human-in-the-loop decision-making to progressively eliminate irrelevant data items while preserving information pertinent to the user's evolving information needs.
18
Publications
724
Citations
107
Authors
43
Institutions
Publications per year
2017–2026
5
Parents
18
1–5 of 18
107
1
h-index
1
h-index
1
h-index
1
h-index
1
h-index
1–5 of 107
43
Ospedale "Santa Maria delle Croci" di Ravenna
Ravenna, Italy
1 h-index
8 publications
136 citations
University of Applied Sciences Mainz
Mainz, Germany
1 h-index
2 publications
34 citations
Max Planck Institute for Chemistry
Mainz, Germany
1 h-index
2 publications
34 citations
Max Planck Society
Munich, Germany
1 h-index
2 publications
380 citations

École Centrale de Lille
Villeneuve-d'Ascq, France
1 h-index
2 publications
42 citations
Institute of Geosciences
Tirana, Albania
1 h-index
1 publications
17 citations
Software602 (Czechia)
Prague, Czechia
1 h-index
3 publications
84 citations
Columbia University
New York, United States
1 h-index
1 publications
17 citations
1–8 of 43
PASP · 3 publications · 330 citations
3
h-index
2 publications · 102 citations
2
h-index
AJ · 1 publications · 35 citations
1
h-index
1 publications · 15 citations
1
h-index
1 publications · 20 citations
1
h-index
1–5