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Genetic Epidemiology, 1999
AbstractThe identification of genes contributing to variation in complex phenotypes requires genetic data of high fidelity. Thus, the identification of pedigree and genotyping errors is a crucial prerequisite to the analysis of data from a genome scan for disease genes.
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AbstractThe identification of genes contributing to variation in complex phenotypes requires genetic data of high fidelity. Thus, the identification of pedigree and genotyping errors is a crucial prerequisite to the analysis of data from a genome scan for disease genes.
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2014
Data cleaning is, in fact, a lively subject that has played an important part in the history of data management and data analytics, and it still is undergoing rapid development. Moreover, data cleaning is considered as a main challenge in the era of big data, due to the increasing volume, velocity and variety of data in many applications.
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Data cleaning is, in fact, a lively subject that has played an important part in the history of data management and data analytics, and it still is undergoing rapid development. Moreover, data cleaning is considered as a main challenge in the era of big data, due to the increasing volume, velocity and variety of data in many applications.
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Proceedings of the 2016 International Conference on Management of Data, 2016
Detecting and repairing dirty data is one of the perennial challenges in data analytics, and failure to do so can result in inaccurate analytics and unreliable decisions. Over the past few years, there has been a surge of interest from both industry and academia on data cleaning problems including new abstractions, interfaces, approaches for ...
Xu Chu +3 more
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Detecting and repairing dirty data is one of the perennial challenges in data analytics, and failure to do so can result in inaccurate analytics and unreliable decisions. Over the past few years, there has been a surge of interest from both industry and academia on data cleaning problems including new abstractions, interfaces, approaches for ...
Xu Chu +3 more
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2002
Multi-source information systems, such as data warehouses, are composed of a set of heterogeneous and distributed data sources. The relevant information is extracted from these sources, cleaned, transformed and then integrated. The confrontation of two different data sources may reveal different kinds of heterogeneities: at the intensional level, the ...
Kedad, Zoubida, Metais, Elisabeth
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Multi-source information systems, such as data warehouses, are composed of a set of heterogeneous and distributed data sources. The relevant information is extracted from these sources, cleaned, transformed and then integrated. The confrontation of two different data sources may reveal different kinds of heterogeneities: at the intensional level, the ...
Kedad, Zoubida, Metais, Elisabeth
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Querying and Cleaning Uncertain Data
2009The management of uncertainty in large databases has recently attracted tremendous research interest. Data uncertainty is inherent in many emerging and important applications, including locationbased services, wireless sensor networks, biometric and biological databases, and data stream applications.
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Mechanism and application of laser cleaning: A review
Optics and Lasers in Engineering, 2022Guodong Zhu, Bin Guo
exaly
Abstract If “data is the new oil,” then corruption in the data used to train artificial intelligence (AI) constitutes a new form of pollution. Environmental AI has traditionally been discussed in terms of its indirect effects on the environment—the irony of burning power, processor cycles, and heat to produce solutions to stop and ...
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Fouling and Chemical Cleaning of Microfiltration Membranes: A Mini-Review
Polymers, 2021Aysegul Gul +2 more
exaly