A systematic review of data quality issues in knowledge discovery tasks

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David Camilo Corrales
Agapito Ismael Ledezma
Juan Carlos Corrales

Abstract

Large volume of data is growing because the organizations are continuously capturing the collective amount of data for better decision-making process. The most fundamental challenge is to explore the large volumes of data and extract useful knowledge for future actions through knowledge discovery tasks, nevertheless many data has poor quality. We presented a systematic review of the data quality issues in knowledge discovery tasks and a case study applied to agricultural disease named coffee rust.

Article Details

How to Cite

[1]
D. C. Corrales, A. I. Ledezma, and J. C. Corrales, “A systematic review of data quality issues in knowledge discovery tasks”, rev.ing.univ.Medellin, vol. 15, no. 28, pp. 125–149, Nov. 2015, doi: 10.22395/rium.v15n28a7.

References

Author Biography

David Camilo Corrales, Universidad del Cauca - Universidad Carlos III de Madrid

Estudiante Candidato de Doctorado en Ingeniería Telemática - Ciencia y Tecnología Informática.

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