Los Angeles, CA
March 31, 2009 to April 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.908
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. This whole procedure is named "Data SPA (Data Systematic Purifying Analysis)". Therefore, the purpose of this research is to evaluate the structure of the data when the data has been systematic purifying analysis. This research has used three kinds of methods to examine the data. After the assessment of the data, the behavior of the data is unsatisfactory. However, using the imputation and functional mapping makes the database add value and increase the amount of information of the data. Data systematic purifying analysis really has its effect because the increase of the amount of information is good for the database that will carry on data mining.
Data mining, Systematic purifying analysis
Yu-Ting Cheng, Ben-Chang Shia, Jun-Yuan Kuo, Hui-Ru Yang, "Data Systematic Purifying Analysis in Data Mining", CSIE, 2009, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, pp. 287-290, doi:10.1109/CSIE.2009.908