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Keyword

data cleaning

Description: Data cleaning is the process of identifying and correcting, removing, or managing inaccurate, incomplete, inconsistent, or unwanted data.
Wikidata ID: wiki/Q1172378
OpenAlex ID: keywords/data-cleaning
Survey Research Methods.
1985 · Susan Losh-Hesselbart, Floyd J. Fowler · Journal of the American Statistical Association · 4,764
A study of the behavior of several methods for balancing machine learning training data
2004 · Gustavo E. A. P. A. Batista, Ronaldo C. Prati, et al. · ACM SIGKDD Explorations Newsletter · 4,216
A Survey of Outlier Detection Methodologies
2004 · Victoria J. Hodge, Jim Austin · Artificial Intelligence Review · 3,590
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An overview of data warehousing and OLAP technology
1997 · Surajit Chaudhuri, Umeshwar Dayal · ACM SIGMOD Record · 2,423
Analysis of Messy Data
1992 · George A. Milliken, Dallas E. Johnson · Thammasat University Digital Collections · 1,468
Data Cleaning: Problems and Current Approaches.
2000 · Erhard Rahm, Hai Hong · 1,467
How to track and assess genotyping errors in population genetics studies
2004 · A. BONIN, E. BELLEMAIN, et al. · Molecular Ecology · 1,417
Data Preprocessing in Data Mining
2014 · Salvador García, Julián Luengo, et al. · Intelligent systems reference library · 1,372
Data preparation for data mining
1999 · Dorian Pyle · 1,364
Methods for the detection of carelessly invalid responses in survey data
2015 · Paul G. Curran · Journal of Experimental Social Psychology · 1,349
A review: Data pre-processing and data augmentation techniques
2022 · Kiran Maharana, Surajit Mondal, et al. · Global Transitions Proceedings · 1,328
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Methodologies for data quality assessment and improvement
2009 · Carlo Batini, Cinzia Cappiello, et al. · ACM Computing Surveys · 1,294
CoordinateCleaner : Standardized cleaning of occurrence records from biological collection databases
2019 · Alexander Zizka, Daniele Silvestro, et al. · Methods in Ecology and Evolution · 1,227
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MegaDepth: Learning Single-View Depth Prediction from Internet Photos
2018 · Zhengqi Li, Noah Snavely · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 1,166
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Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications
2022 · Shanaka Kristombu Baduge, Sadeep Thilakarathna, et al. · Automation in Construction · 1,001
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VIIRS night-time lights
2017 · Christopher D Elvidge, Kimberly Baugh, et al. · International Journal of Remote Sensing · 983
GGIR: A Research Community–Driven Open Source R Package for Generating Physical Activity and Sleep Outcomes From Multi-Day Raw Accelerometer Data
2019 · Jairo H. Migueles, Alex V. Rowlands, et al. · Journal for the Measurement of Physical Behaviour · 955
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Adaptive duplicate detection using learnable string similarity measures
2003 · Mikhail Bilenko, Raymond J. Mooney · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · 930
Tidy Data
2014 · Hadley Wickham · Journal of Statistical Software · 904
The Pushshift Reddit Dataset
2020 · Jason Baumgartner, Savvas Zannettou, et al. · Proceedings of the International AAAI Conference on Web and Social Media · 865
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Trust, But Verify: On the Importance of Chemical Structure Curation in Cheminformatics and QSAR Modeling Research
2010 · Denis Fourches, Eugene Muratov, et al. · Journal of Chemical Information and Modeling · 829
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Analyzing Microarray Gene Expression Data
2004 · Geoffrey J. McLachlan, Kim‐Anh Do, et al. · Wiley series in probability and statistics · 826
Real-world Data is Dirty: Data Cleansing and The Merge/Purge Problem
1998 · Mauricio A. Hernández, Salvatore J. Stolfo · Data Mining and Knowledge Discovery · 813
The SAGE Handbook of Social Media Research Methods
2016 · Luke Sloan, Anabel Quan-Haase · SAGE Publications Ltd eBooks · 775
Which h-index? — A comparison of WoS, Scopus and Google Scholar
2007 · Judit Bar-Ilan · Scientometrics · 728
Works count: 18,550
Citation count: 176,200
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