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Data-oriented applications, their users, and even the law require data of high quality.
A value for n-person games
Lloyd S Shapley · 1953
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Representative sampling, III: The current statistical literature
William Kruskal and Frederick Mosteller · 1979
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A comparative analysis of methodologies for database schema integration
Carlo Batini, Maurizio Lenzerini, and Shamkant B. Navathe · 1986
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Beyond accuracy: What data quality means to data consumers
Richard Y. Wang and Diane M. Strong · 1996
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Using schema matching to simplify heterogeneous data translation
Tova Milo and Sagit Zohar · 1998
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Assessment methods for information quality criteria
Felix Naumann and Claudia Rolker · 2000
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A survey of approaches to automatic schema matching
Erhard Rahm and Philip A. Bernstein · 2001
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Data quality: the field guide
Thomas C Redman · 2001
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Towards semantic web mining
Bettina Berendt, Andreas Hotho, and Gerd Stumme · 2002
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Data quality assessment
Leo L. Pipino, Yang W. Lee, and Richard Y. Wang · 2002
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Information retrieval on the semantic web
Urvi Shah, Timothy W. Finin, and Anupam Joshi · 2002
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k-anonymity: A model for protecting privacy
Latanya Sweeney · 2002
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Information retrieval: algorithms and heuristics
David A. Grossman and Ophir Frieder · 2004
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Sample-based quality estimation of query results in relational database environments
Donald P Ballou, InduShobha N Chengalur-Smith, and Richard Y Wang · 2006
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Data quality: concepts, methodologies and techniques
Carlo Batini and Monica Scannapieco · 2006
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Differential privacy
Cynthia Dwork · 2006
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Data provenance: A categorization of existing approaches
Boris Glavic and Klaus R. Dittrich · 2007
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Data quality and record linkage techniques
Thomas N. Herzog, Fritz Scheuren, and William E. Winkler · 2007
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Data quality assessment
Arkady Maydanchik · 2007
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Intensional associations between data and metadata
Divesh Srivastava and Yannis Velegrakis · 2007
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A framework for information quality assessment
Besiki Stvilia, Les Gasser, Michael B. Twidale, and Linda C. Smith · 2007
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Learning from imbalanced data
Haibo He and Edwardo A. Garcia · 2008
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Methodologies for data quality assessment and improvement
Carlo Batini, Cinzia Cappiello, Chiara Francalanci, and Andrea Maurino · 2009
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Square-aligned data quality model for web portals
Carmen Moraga, María Ángeles Moraga, Coral Calero, and Angélica Caro · 2009
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An introduction to duplicate detection
Felix Naumann and Melanie Herschel · 2010
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On accuracy of PDF divergence estimators and their applicability to representative data sampling
Marcin Budka, Bogdan Gabrys, and Katarzyna Musial · 2011
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Data Matching - Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection
Peter Christen · 2012
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Principles of Data Integration
AnHai Doan, Alon Halevy, and Zachary Ives · 2012
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NADEEF: a commodity data cleaning system
Michele Dallachiesa, Amr Ebaid, Ahmed Eldawy, Ahmed K. Elmagarmid, Ihab F. Ilyas, Mourad Ouzzani, and Nan Tang · 2013
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The curse of dimensionality in data quality
Vimukthi Jayawardene, Shazia W. Sadiq, and Marta Indulska · 2013
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Data profiling revisited
Felix Naumann · 2013
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Handbook of data quality: research and practice
Shazia Sadiq, editor · 2013
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Estimating the number and sizes of fuzzy-duplicate clusters
Arvid Heise, Gjergji Kasneci, and Felix Naumann · 2014
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The many Shapley values for model explanation
Mukund Sundararajan and Amir Najmi · 2020
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Missing data patterns: From theory to an application in the steel industry
Michal Bechny, Florian Sobieczky, Jürgen Zeindl, and Lisa Ehrlinger · 2021
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Data catalogs: A systematic literature review and guidelines to implementation
Lisa Ehrlinger, Johannes Schrott, Martin Melichar, Nicolas Kirchmayr, and Wolfram Wöß · 2021
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Estimating the extent of the effects of data quality through observations
Daniele Foroni, Matteo Lissandrini, and Yannis Velegrakis · 2021
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The right to data portability: conception, status quo, and future directions
Sophie Kuebler-Wachendorff, Robert Luzsa, Johann Kranz, Stefan Mager, Emmanuel Syrmoudis, Susanne Mayr, and Jens Grossklags · 2021
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Ziawasch Abedjan, Lukasz Golab, and Felix Naumann · 2015
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The challenges of data quality and data quality assessment in the big data era
Li Cai and Yangyong Zhu · 2015
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Iso/iec 25024:2015 systems and software engineering – systems and software quality requirements and evaluation (square) – measurement of data quality
International Organization for Standardization · 2015
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Bigdansing: A system for big data cleansing
Zuhair Khayyat, Ihab F. Ilyas, Alekh Jindal, Samuel Madden, Mourad Ouzzani, Paolo Papotti, Jorge-Arnulfo Quiané-Ruiz, Nan Tang, and Si Yin · 2015
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DBpedia - A large-scale, multilingual knowledge base extracted from wikipedia
Jens Lehmann, Robert Isele, Max Jakob, Anja Jentzsch, Dimitris Kontokostas, Pablo N. Mendes, Sebastian Hellmann, Mohamed Morsey, Patrick van Kleef, Sören Auer, and Christian Bizer · 2015
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Data and Information Quality: Dimensions, Principles and Techniques
Carlo Batini and Monica Scannapieco · 2016
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Peng Li, Xi Rao, Jennifer Blase, Yue Zhang, Xu Chu, and Ce Zhang · 2021
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Measuring biological diversity
Anne E. Magurran · 2021
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From cleaning before ML to cleaning for ML
Felix Neutatz, Binger Chen, Ziawasch Abedjan, and Eugene Wu · 2021
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The chinese approach to artificial intelligence: an analysis of policy, ethics, and regulation
Huw Roberts, Josh Cowls, Jessica Morley, Mariarosaria Taddeo, Vincent Wang, and Luciano Floridi · 2021
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Reliable post hoc explanations: Modeling uncertainty in explainability
Dylan Slack, Anna Hilgard, Sameer Singh, and Himabindu Lakkaraju · 2021
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The effects of data quality on machine learning performance
Lukas Budach, Moritz Feuerpfeil, Nina Ihde, Andrea Nathansen, Nele Noack, Hendrik Patzlaff, Hazar Harmouch, and Felix Naumann · 2022
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Data representativity for machine learning and AI systems
Line H. Clemmensen and Rune D. Kjærsgaard · 2022
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Data cleaning and automl: Would an optimizer choose to clean?
Felix Neutatz, Binger Chen, Yazan Alkhatib, Jingwen Ye, and Ziawasch Abedjan · 2022
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Data cards: Purposeful and transparent dataset documentation for responsible AI
Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson · 2022
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Dsd: the data source description vocabulary
Lisa Ehrlinger, Johannes Schrott, and Wolfram Wöß · 2023
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How large language models will disrupt data management
Raul Castro Fernandez, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan, and Chenhao Tan · 2023
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Executive order on the safe, secure, and trustworthy development and use of artificial intelligence, 2023
The White House · 2023
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Data collection and quality challenges in deep learning: a data-centric AI perspective
Steven Euijong Whang, Yuji Roh, Hwanjun Song, and Jae-Gil Lee · 2023
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Data-centric artificial intelligence: A survey
Daochen Zha, Zaid Pervaiz Bhat, Kwei-Herng Lai, Fan Yang, Zhimeng Jiang, Shaochen Zhong, and Xia Hu · 2023
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URL https://www.europarl.europa.eu/topics/en/article/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence
EU AI act: first regulation on artificial intelligence, 2023 · 2024
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URL https://www.federalregister.gov/documents/2024/04/26/2024-08503/hipaa-privacy-rule-to-support-reproductive-health-care-privacy
HIPAA privacy rule to support reproductive health care privacy, 2024a · 2024
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URL https://www.kaggle.com/
Kaggle: Your machine learning and data science community, 2024b · 2024
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URL https://www.wikipedia.org/
Wikipedia, the free encyclopedia, 2024c · 2024
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Croissant: A metadata format for ml-ready datasets
Mubashara Akhtar, Omar Benjelloun, Costanza Conforti, Pieter Gijsbers, Joan Giner-Miguelez, Nitisha Jain, Michael Kuchnik, Quentin Lhoest, Pierre Marcenac, Manil Maskey, Peter Mattson, Luis Oala, Pierre Ruyssen, Rajat Shinde, Elena Simperl, Goeffry Thomas, Slava Tykhonov, Joaquin Vanschoren, Jos van der Velde, Steffen Vogler, and Carole-Jean Wu · 2024
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Artifical inteligence act
European Parliament · 2024
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How do categorical duplicates affect ML? a new benchmark and empirical analyses
Vraj Shah, Thomas Parashos, and Arun Kumar · 2024
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