Duplicate Content Detection
Duplicate Content Detection is a computational method designed to identify substantively similar or verbatim instances of web content across digital sources, distinguishing itself from related content analysis techniques through its specific focus on detecting exact or near-identical replications that may affect search engine indexing and ranking.
104
Publications
5.1K
Citations
331
Authors
146
Institutions
Publications per year
2017–2026
26
Parents
104
Nick Koudas, Sunita Sarawagi, Divesh Srivastava · 2006 · 292 citations
Howard B. Newcombe, J.M. Kennedy · Communications of the ACM · 1962 · 209 citations
Halbert L. Dunn · American Journal of Public Health and the Nations Health · 1946 · 168 citations
First story detection in TDT is hard
James Allan, Victor Lavrenko, Hubert Jin · 2000 · 162 citations · Full text
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Microsoft Research Asia (China)
Beijing, China
7 h-index
21 publications
839 citations

Chinese Academy of Sciences
Beijing, China
4 h-index
10 publications
789 citations
Technion – Israel Institute of Technology
Haifa, Israel
3 h-index
6 publications
294 citations
Stanford Medicine
Stanford, United States
3 h-index
8 publications
908 citations

University of Waterloo
Waterloo, Canada
3 h-index
5 publications
243 citations
Politecnico di Milano
Milan, Italy
3 h-index
11 publications
316 citations
Universidade Federal de Minas Gerais
Belo Horizonte, Brazil
3 h-index
10 publications
335 citations
University of Chinese Academy of Sciences
Beijing, China
3 h-index
7 publications
295 citations
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TKDE · 4 publications · 210 citations
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3 publications · 135 citations
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Repository · 2 publications · 60 citations
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2 publications · 40 citations
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2 publications · 110 citations
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