Data Quality Mining

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2019

Autores

Alexandra Oliveira (Autor) Outra; Rita Gaio (Autor) Outra; Pilar Baylina (Autor) Outra; Carlos Rebelo (Autor) Outra; Luís Paulo Reis (Autor) FEUP

Ata de Conferência Internacional

Título: New knowledge in information systems and technologies

Páginas: 361-372

WorldCIST 2019: World Conference on Information Systems and Technologies

Galicia, 16 a 19 de abril de 2019

Indexação

Scopus - 1 Citação

Outras Informações

ID Authenticus: P-00Q-GSB

DOI: 10.1007/978-3-030-16181-1_34

Abstract (EN): We are living in a world of information abundance, surplus, and access. We have technologies to acquire any type of information but we still face the challenge of extracting the underlying valuable knowledge. Data analyses and mining processes may be severely impaired whenever data are corrupted by noise, ambiguity and distortions. This paper aims to provide a systematic procedure for data cleaning in single files data sources without schema that may be corrupted by the most common data problems. The methodology is guided by the dimensions of data quality standards and focuses on the goal of performing reasonable posterior statistical analyses. © 2019, Springer Nature Switzerland AG.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 12