Data Discrepancy Detection
Data Discrepancy Detection is a systematic methodological framework within data quality assessment that identifies and characterizes inconsistencies, anomalies, or deviations in datasets by comparing observed data against established expectations, constraints, or reference standards.
48
Publications
2.8K
Citations
157
Authors
84
Institutions
Publications per year
2017–2026
17
Parents
48
1–5 of 48
157
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h-index
University of Illinois Urbana-Champaign, United States
2 publications · 36 citations
2
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2
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2
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2
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1–5 of 157
84

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
2 h-index
3 publications
290 citations
University of Cambridge
Cambridge, United Kingdom
2 h-index
2 publications
60 citations
Humboldt-Universität zu Berlin
Berlin, Germany
2 h-index
4 publications
64 citations

Imperial College London
London, United Kingdom
1 h-index
2 publications
144 citations
Rutgers, The State University of New Jersey
New Brunswick, United States
1 h-index
1 publications
122 citations

National Physical Laboratory
London, United Kingdom
1 h-index
3 publications
78 citations

University of Massachusetts Amherst
Amherst Center, United States
1 h-index
2 publications
56 citations

Mahidol University
Bangkok, Thailand
1 h-index
1 publications
31 citations
1–8 of 84
2 publications · 84 citations
2
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2 publications · 36 citations
2
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1 publications · 23 citations
1
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Conference · 1 publications · 37 citations
1
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1 publications · 19 citations
1
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