Dictionary-Based Fast Transform for Text Compression with High Compression Ratio

In this paper we introduce a dictionary-based fast lossless text transform algorithm. This algorithm utilizes ternary search tree to expedite transform encoding operation. Based on an efficient dictionary mapping model, this algorithm use a fast hash function to achieve a lightening speed in the transform decoding phrase. Results shows that the average compression time using the transform algorithm with bzip2 -9 , gzip 9 and PPMD is 28.1% slower, 50.4% slower and 21.2% faster compared to the original bzip2 -9 , gzip -9 and PPMD respectively. Meanwhile, the overhead in the decompression phrase is negligible. Facilitated with our proposed transform algorithm, bzip2 –9 and PPMD both achieve a better compression performance than most of the improvements on the BWT and PPM based compression algorithms. Especially, we get the conclusion that Bzip2 in conjunction with this transform is better than PPMD both in time complexity and compression performance. This transform is especially suitable for domainspecific lossless text compression.