A data mining approach to improve the automated quality of data
Alkharboush, Nawaf Abdullah H. (2014) A data mining approach to improve the automated quality of data. PhD thesis, Queensland University of Technology.
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.
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|Item Type:||QUT Thesis (PhD)|
|Supervisor:||Li, Yuefeng, Bruce, Christine, & Nayak, Richi|
|Keywords:||Data Mining, Granule Mining, Data Quality, Outlier Detection, Quality Assessment, Noise Detection, Data Cleaning|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Institution:||Queensland University of Technology|
|Deposited On:||08 Jan 2014 05:16|
|Last Modified:||07 Sep 2015 01:03|
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