Please use this identifier to cite or link to this item: http://dspace.univ-guelma.dz/jspui/handle/123456789/13181
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dc.contributor.authorHEMAIZIA, BASSEM-
dc.date.accessioned2022-10-12T13:06:14Z-
dc.date.available2022-10-12T13:06:14Z-
dc.date.issued2022-
dc.identifier.urihttp://dspace.univ-guelma.dz/jspui/handle/123456789/13181-
dc.description.abstractThis work revolves around quality control of NoSQL data, specifically document-oriented data. In fact, it relies on a method that allows to detect and repair the problems of schematic overlap, duplication, and incompleteness based on the frequency of database elements. For this purpose, a new method named MFU (Most Frequently Used) has been proposed. The MFU method consists of three phases: (1) quality problem detection, (2) data repair, and (3) quality verification. In each phase, three types of data quality problems are addressed. Our MFU method has been validated by implementing the Quality of Document oriented Database (QoDB) tool and evaluated on the MongoDB COVID19 database that was released in 2022. The results obtained are interesting.en_US
dc.language.isofren_US
dc.publisheruniversité de guelmaen_US
dc.subjectQualité de données, données NoSQL, MongoDB, Détection des problèmes, Réparation, Vérification.en_US
dc.titleContrôle de qualité de données NoSQLen_US
dc.typeWorking Paperen_US
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