Data mining approach to evaluate the data lossless Data Compression algorithms
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2012, Vol 1, Issue 8
Abstract
: This paper presents a study of various lossless compression algorithms; to test the performance and the ability of compression of each algorithm based on ten different parameters. For evaluation the compression ratios of each algorithm on different parameters are processed. To classify the algorithms based on the compression ratio, rule base is constructed to mine with frequent bit pattern to analyze the variations in various compression algorithms. Also, enhanced K- Medoid clustering is used to cluster the various data compression algorithms based on various parameters. The cluster falls dissentingly high to low after the enhancement. The framed rule base consists of 1,296 rules, which is used to evaluate the compression algorithm. Hundred and eighty four Compression algorithms are used for this study. The experimental result shows only few algorithm satisfies the range “High” for more number of parameters.
Authors and Affiliations
Nishad P. M. Ph. D Scholar, , Dr. R. Manicka chezian
Keywords
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