Interactive Query Refinement
Interactive Query Refinement is a visual querying method that enables users to iteratively modify and narrow spatial query parameters through real-time graphical interactions to improve result accuracy and relevance.
56
Publications
5.4K
Citations
179
Authors
78
Institutions
Publications per year
2017–2026
5
56
Support vector machine active learning for image retrieval
Simon Tong, Edward Yi Chang · 2001 · 1.3K citations
Mining anchor text for query refinement
Reiner Kraft, Jason Y. Zien · 2004 · 171 citations
1–5 of 56
179
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h-index
FZI Research Center for Information Technology, Germany
3 publications · 58 citations
3
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3
h-index
FZI Research Center for Information Technology, Germany
3 publications · 58 citations
3
h-index
2
h-index
1–5 of 179
78

University of Regina
Regina, Canada
4 h-index
9 publications
200 citations
University of California, Santa Barbara
Santa Barbara, United States
3 h-index
3 publications
1.8K citations
University of Maryland, College Park
College Park, United States
3 h-index
9 publications
529 citations
RWTH Aachen University
Aachen, Germany
3 h-index
15 publications
447 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
4 publications
225 citations
Northeastern University
Boston, United States
2 h-index
3 publications
38 citations
Université de Montréal
Montreal, Canada
2 h-index
2 publications
108 citations
Arizona State University
Tempe, United States
2 h-index
3 publications
171 citations
1–8 of 78
2 publications · 36 citations
2
h-index
2 publications · 51 citations
2
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PVLDB · 2 publications · 80 citations
2
h-index
1 publications · 23 citations
1
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AAI · 1 publications · 20 citations
1
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1–5