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 | |
| 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 | United States |
| City | Los Angeles, CA |
| Period | 3/31/09 → 4/2/09 |
Fingerprint
ASJC Scopus subject areas
- Computer Science Applications
- Hardware and Architecture
- Information Systems
- Software
Cite this
Data systematic purifying analysis in data mining. / Cheng, Yu Ting; Shia, Ben Chang; Kuo, Jun Yuan; Yang, Hui Ru.
2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009. Vol. 4 2009. p. 287-290 5171004.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
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
VL - 4
SP - 287
EP - 290
BT - 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009
ER -