Iterative Selection Processes
Iterative Selection Processes is a methodological framework in artifact selection that systematically refines candidate artifacts through repeated cycles of evaluation and feedback to progressively converge on optimal or satisfactory solutions.
142
Publications
10.4K
Citations
554
Authors
296
Institutions
Publications per year
2017–2026
48
Parents
142
DNA Solution of the Maximal Clique Problem
Qi Ouyang, Peter D. Kaplan, Shumao Liu et al. · Science · 1997 · 624 citations
An evaluation on feature selection for text clustering
Tao Liu, Shengping Liu, Zheng Chen et al. · 2003 · 246 citations
1–5 of 142
554
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Nanjing University of Information Science and Technology, China
2 publications · 118 citations
2
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2
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2
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1–5 of 554
296

University of Toronto
Toronto, Canada
4 h-index
7 publications
348 citations

Cornell University
Ithaca, United States
3 h-index
4 publications
152 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
7 publications
154 citations

Johns Hopkins University
Baltimore, United States
3 h-index
10 publications
336 citations
National University of Singapore
Singapore, Singapore
3 h-index
4 publications
193 citations
University of Southern California
Los Angeles, United States
3 h-index
5 publications
189 citations
University of California, Los Angeles
Los Angeles, United States
3 h-index
10 publications
665 citations
Texas A&M University
College Station, United States
3 h-index
5 publications
348 citations
1–8 of 296
GRSL · 3 publications · 374 citations
3
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3 publications · 144 citations
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3 publications · 340 citations
3
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3 publications · 254 citations
3
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2 publications · 30 citations
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