Search Space Pruning
Search Space Pruning is a computational strategy within search and optimization methodologies that systematically reduces the set of possible solutions by eliminating infeasible or suboptimal regions of the search space, thereby improving efficiency without compromising the optimality or accuracy of the final outcome.
1.2K
Publications
66K
Citations
3.3K
Authors
981
Institutions
Publications per year
2017–2026
301
1.2K
Sequential PAttern mining using a bitmap representation
Jay Ayres, Jason Flannick, Johannes Gehrke et al. · 2002 · 1.1K citations
Searching protein structure databases with DaliLite v.3
Liisa Holm, Sakari Kääriäinen, Päivi Rosenström et al. · Bioinformatics · 2008 · 1K citations · Full text
GRASP - A New Search Algorithm for Satisfiability
1996 · 860 citations
1–5 of 1.2K
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Hong Kong University of Science and Technology, Hong Kong SAR China
9 publications · 622 citations
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1–5 of 3.3K
981
University of Illinois Urbana-Champaign
Urbana, United States
18 h-index
41 publications
2.6K citations
University of Michigan
Ann Arbor, United States
17 h-index
35 publications
3.5K citations
Tsinghua University
Beijing, China
16 h-index
56 publications
2.8K citations
National University of Singapore
Singapore, Singapore
14 h-index
33 publications
2.3K citations
Carnegie Mellon University
Pittsburgh, United States
14 h-index
30 publications
1.1K citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
14 h-index
26 publications
2.3K citations

Harbin Institute of Technology
Harbin, China
13 h-index
26 publications
1.6K citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
13 h-index
27 publications
1.2K citations
1–8 of 981
TKDE · 42 publications · 2.8K citations
29
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Repository · 35 publications · 828 citations
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PVLDB · 19 publications · 1.9K citations
16
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Conference · 14 publications · 431 citations
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Conference · 11 publications · 524 citations
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