DocumentCode
2487365
Title
Notice of Retraction
The Research of Outlier Data Cleaning through Relevance Comparison
Author
Wang Heyong
Author_Institution
Coll. of E-Bus., South China Univ. of Technol., Guangzhou, China
fYear
2010
fDate
22-23 May 2010
Firstpage
1
Lastpage
3
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In view of the data integration process, it puts forward the relevance comparison in outlier data cleaning in this paper. Namely in the data integration process, outlier data is discovered in certain fields through the relevant comparison. It can change the detection of outlier data, improve the data quality in the data integration process, enhance data availability. At the end of this article, it gives a specific description of the algorithm and interface of data cleaning results.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In view of the data integration process, it puts forward the relevance comparison in outlier data cleaning in this paper. Namely in the data integration process, outlier data is discovered in certain fields through the relevant comparison. It can change the detection of outlier data, improve the data quality in the data integration process, enhance data availability. At the end of this article, it gives a specific description of the algorithm and interface of data cleaning results.
Keywords
data mining; data availability; data integration process; outlier data cleaning; relevance comparison; Change detection algorithms; Cleaning; Clustering algorithms; Educational institutions; Explosives; Information systems; Information technology; Inspection; Nearest neighbor searches; Production;
fLanguage
English
Publisher
ieee
Conference_Titel
e-Business and Information System Security (EBISS), 2010 2nd International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-5893-6
Type
conf
DOI
10.1109/EBISS.2010.5473717
Filename
5473717
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