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E-Clean: A Data Cleaning Framework for Patient Data
2011 First International Conference on Informatics and Computational Intelligence, 2011We need to prepare quality data by pre-processing the raw data. Data cleaning, also called data cleansing or scrubbing, deals with detecting and removing errors and inconsistencies from data in order to improve the quality of data. Data cleaning system are needed to support any changes in the structure, representation or content of data.
Hasimah Hj Mohamed +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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This document from Sinclair Community College explores data cleaning. Examples of dirty data, data storage, vocabulary terms related to data cleaning, cleaning using Excel, cleaning using Python, and two data cleaning activities are highlighted.&
Robert Nisbet +2 more
core +4 more sources
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.
openaire +2 more sources
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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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, 2022Debin Shan, Zhenhai Xu, Bin Guo
exaly
Fouling and Chemical Cleaning of Microfiltration Membranes: A Mini-Review
Polymers, 2021Fatma Yalçınkaya +2 more
exaly