Experimental Analysis on the Performance of a New Preprocessing Method Used in Data Compression

This paper presents a new text transformation method, which has a few similarities with the StarNT text transformation method. StarNT is a dictionary-based lossless text transform algorithm. Many different compression methods have been devised by researchers to find a suitable solution of data transmission that utilises the entire network bandwidth optimally and which also achieves a higher compression ratio. Most of the approaches that are being used, like the Prediction by Partial Matching (PPM), Burrows-Wheeler Transform have been unable to achieve the best possible output as provided by theoretical calculations and hence have left researchers to find more efficient techniques of text compression. Further in this paper we also provide the experimental results of the timing performance and space utilisation by compression of our algorithm by comparing with StarNT method.