Data systematic purifying analysis in data mining

Yu Ting Cheng; Ben Chang Shia; Jun Yuan Kuo; Hui Ru Yang

doi:10.1109/CSIE.2009.908

Data systematic purifying analysis in data mining

Yu Ting Cheng, Ben Chang Shia, Jun Yuan Kuo, Hui Ru Yang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A goal database and an auxiliary database utilizing functional mapping make the database combine as a great database, then imputes the missing data or the rare data missing in the database. In order to improve the data analysis efficiency, this research proposed the Data SPA (Data Systematic Purifying Analysis) to purify the data systematically. This research has applied three kinds of methods to evaluate the data. After the process of the Data SPA, it can be easily understand that the Data SPA really has good effect on data mining, because it can increase the amount of information of the data and improve the data evaluation efficiency.

Original language	English
Title of host publication	2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009
Pages	287-290
Number of pages	4
Volume	4
DOIs	https://doi.org/10.1109/CSIE.2009.908
Publication status	Published - 2009
Externally published	Yes
Event	2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009 - Los Angeles, CA, United States Duration: Mar 31 2009 → Apr 2 2009

Other

Other	2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009
Country/Territory	United States
City	Los Angeles, CA
Period	3/31/09 → 4/2/09

ASJC Scopus subject areas

Computer Science Applications
Hardware and Architecture
Information Systems
Software

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10.1109/CSIE.2009.908

Cite this

Cheng, YT, Shia, BC, Kuo, JY & Yang, HR 2009, Data systematic purifying analysis in data mining. in 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009. vol. 4, 5171004, pp. 287-290, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, Los Angeles, CA, United States, 3/31/09. https://doi.org/10.1109/CSIE.2009.908

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year = "2009",

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AB - A goal database and an auxiliary database utilizing functional mapping make the database combine as a great database, then imputes the missing data or the rare data missing in the database. In order to improve the data analysis efficiency, this research proposed the Data SPA (Data Systematic Purifying Analysis) to purify the data systematically. This research has applied three kinds of methods to evaluate the data. After the process of the Data SPA, it can be easily understand that the Data SPA really has good effect on data mining, because it can increase the amount of information of the data and improve the data evaluation efficiency.

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ER -

Data systematic purifying analysis in data mining

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