DocumentCode
2185187
Title
Minability through Compression
Author
Simovici, D.A.
Author_Institution
Dept. of Comput. Sci., Univ. of Massachusetts Boston, Boston, MA, USA
fYear
2013
fDate
23-26 Sept. 2013
Firstpage
32
Lastpage
36
Abstract
We offer an experimental proof that the application of compression to data files can be used as a evaluation technique for minability of the data. This is based on the fact that the presence of patterns embedded in data has an influence of compressibility.
Keywords
data compression; data mining; data compressibility; data file compression; data minability evaluation technique; Association rules; Compression algorithms; Correlation; Entropy; Probability distribution; Random variables; Kronecker product; LZW; data mining; lossless compression; market basket data; patterns;
fLanguage
English
Publisher
ieee
Conference_Titel
Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2013 15th International Symposium on
Conference_Location
Timisoara
Print_ISBN
978-1-4799-3035-7
Type
conf
DOI
10.1109/SYNASC.2013.11
Filename
6821128
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