DocumentCode :
2126767
Title :
Optimal Cleaning Rule Selection Model Design Based on Machine Learning
Author :
Yan Hao ; Diao Xing-Chun
Author_Institution :
.nstitute of Command Autom., PL A Univ.ofSci. & Tech., Nanjing
fYear :
2008
fDate :
21-22 Dec. 2008
Firstpage :
598
Lastpage :
600
Abstract :
Considering the limited extensibility and the uneven capacity of the cleaning rule in current data cleaning work, this paper proposes an optimal cleaning rule selection model based on the machine learning. By establishing a cleaning rule performance evaluation system, the model realizes the optimal cleaning rule selection. It implements dynamic expansion of cleaning rule by the support of rules base. The model ensures the results of the data cleaning process and improves the performance of the data cleaning.
Keywords :
data analysis; data mining; knowledge based systems; learning (artificial intelligence); machine learning; optimal data cleaning rule selection model design; performance evaluation system; rule base support; Cleaning; Data analysis; Humans; Information management; Information processing; Knowledge acquisition; Learning systems; Machine learning; Management information systems; Quality management; cleaning rule; optimal;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3488-6
Type :
conf
DOI :
10.1109/KAM.2008.113
Filename :
4732896
Link To Document :
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