Similarity Detection
Similarity Detection is a data reduction technique that identifies near-duplicate data segments by measuring content resemblance, distinguishing it from exact matching through its reliance on approximate similarity metrics.
1.4K
Publications
74.7K
Citations
3.8K
Authors
1.2K
Institutions
Publications per year
2017–2026
302
Variants
Near-duplicate Detection
Parents
1.4K
Topology matching for fully automatic similarity estimation of 3D shapes
Masaki Hilaga, Yoshihisa Shinagawa, Taku Kohmura et al. · 2001 · 2.2K citations
A modified Hausdorff distance for object matching
Marie-Pierre Dubuisson, A.K. Jain · 2002 · 1.5K citations
1–5 of 1.4K
3.8K
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University of Electronic Science and Technology of China, China
8 publications · 215 citations
8
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8
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1–5 of 3.8K
1.2K
Tsinghua University
Beijing, China
17 h-index
52 publications
2.6K citations
Microsoft (United States)
Redmond, United States
16 h-index
40 publications
2.7K citations
University of Maryland, College Park
College Park, United States
15 h-index
39 publications
2.6K citations

Chinese Academy of Sciences
Beijing, China
15 h-index
38 publications
1.1K citations

UNSW Sydney
Sydney, Australia
14 h-index
31 publications
3.8K citations
National University of Singapore
Singapore, Singapore
14 h-index
29 publications
1K citations

Cornell University
Ithaca, United States
14 h-index
26 publications
1.6K citations
Carnegie Mellon University
Pittsburgh, United States
13 h-index
36 publications
6.6K citations
1–8 of 1.2K
TKDE · 29 publications · 2K citations
21
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PVLDB · 19 publications · 1.3K citations
16
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11 publications · 411 citations
11
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11 publications · 475 citations
11
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13 publications · 303 citations
11
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