Errors of identifiers in anonymous databases: impact on data quality

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.creatorPombinho, Paulo-
Autor(es): dc.creatorCavique, Luís-
Autor(es): dc.creatorCorreia, Luís-
Data de aceite: dc.date.accessioned2025-08-21T15:13:49Z-
Data de disponibilização: dc.date.available2025-08-21T15:13:49Z-
Data de envio: dc.date.issued2023-01-02-
Data de envio: dc.date.issued2023-01-02-
Data de envio: dc.date.issued2022-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/10400.2/12904-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/10400.2/12904-
Descrição: dc.descriptionData quality is essential for a correct understanding of the concepts they represent. Data mining is especially relevant when data with inferior quality is used in algorithms that depend on correct data to create accurate models and predictions. In this work, we introduce the issue of errors of identifiers in an anonymous database. The work proposes a quality evaluation approach that considers individual attributes and a contextual analysis that allows additional quality evaluations. The proposed quality analysis model is a robust means of minimizing anonymization costs.-
Descrição: dc.descriptionThe authors would like to thank the FCT Projetct of Scientific Research and Technological Development in Data Science and Artificial Intelligence in Public Administration, 2018–2022 (DSAIPA/DS/0039/2018), for its support, and also acknowledge support by BioISI (UID/MULTI/04046/2103) and LASIGE Research Unit (UIDB/00408/2020, UIDP/00408/2020) center grants.-
Descrição: dc.descriptionThe authors would like to thank the FCT Projetct of Scientific Research and Technological Development in Data Science and Artificial Intelligence in Public Administration, 2018–2022 (DSAIPA/DS/0039/2018), for its support, and also acknowledge support by BioISI (UID/MULTI/04046/2103) and LASIGE Research Unit (UIDB/00408/2020, UIDP/00408/2020) center grants.-
Descrição: dc.descriptioninfo:eu-repo/semantics/publishedVersion-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Relação: dc.relationLASIGE - Extreme Computing-
Relação: dc.relationLASIGE - Extreme Computing-
Palavras-chave: dc.subjectData pre-processing-
Palavras-chave: dc.subjectAnonymized data-
Palavras-chave: dc.subjectData quality-
Título: dc.titleErrors of identifiers in anonymous databases: impact on data quality-
Aparece nas coleções:Repositório Aberto - Universidade Aberta (Portugal)

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