A data mining approach to improve the automated quality of data
Data(s) |
2014
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Resumo |
This thesis describes the development of a robust and novel prototype to address the data quality problems that relate to the dimension of outlier data. It thoroughly investigates the associated problems with regards to detecting, assessing and determining the severity of the problem of outlier data; and proposes granule-mining based alternative techniques to significantly improve the effectiveness of mining and assessing outlier data. |
Formato |
application/pdf |
Identificador | |
Publicador |
Queensland University of Technology |
Relação |
http://eprints.qut.edu.au/65641/1/Nawaf%20Abdullah%20H_Alkharboush_Thesis.pdf Alkharboush, Nawaf Abdullah H. (2014) A data mining approach to improve the automated quality of data. PhD thesis, Queensland University of Technology. |
Fonte |
School of Electrical Engineering & Computer Science; Science & Engineering Faculty |
Palavras-Chave | #Data Mining #Granule Mining #Data Quality #Outlier Detection #Quality Assessment #Noise Detection #Data Cleaning |
Tipo |
Thesis |