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
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

Publication series

Name	2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009
Volume	4

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

Access to Document

10.1109/CSIE.2009.908

Cite this

Data systematic purifying analysis in data mining. / Cheng, Yu Ting; Shia, Ben Chang; Kuo, Jun Yuan et al.
2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009. 2009. p. 287-290 5171004 (2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009; Vol. 4).

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

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., 5171004, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, vol. 4, 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

@inproceedings{6bf3db66ebb249daa6e6a23f5c337255,

title = "Data systematic purifying analysis in data mining",

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.",

author = "Cheng, {Yu Ting} and Shia, {Ben Chang} and Kuo, {Jun Yuan} and Yang, {Hui Ru}",

year = "2009",

doi = "10.1109/CSIE.2009.908",

language = "English",

isbn = "9780769535074",

series = "2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009",

pages = "287--290",

booktitle = "2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009",

note = "2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009 ; Conference date: 31-03-2009 Through 02-04-2009",

}

TY - GEN

T1 - Data systematic purifying analysis in data mining

AU - Cheng, Yu Ting

AU - Shia, Ben Chang

AU - Kuo, Jun Yuan

AU - Yang, Hui Ru

PY - 2009

Y1 - 2009

N2 - 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.

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.

UR - http://www.scopus.com/inward/record.url?scp=71049144883&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=71049144883&partnerID=8YFLogxK

U2 - 10.1109/CSIE.2009.908

DO - 10.1109/CSIE.2009.908

M3 - Conference contribution

AN - SCOPUS:71049144883

SN - 9780769535074

T3 - 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009

SP - 287

EP - 290

BT - 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009

T2 - 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009

Y2 - 31 March 2009 through 2 April 2009

ER -

Data systematic purifying analysis in data mining

Abstract

Publication series

Other

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this