Universal Text Preprocessing for Data Compression
IEEE Transactions on Computers
Visually Lossless HTML Compression
WISE '09 Proceedings of the 10th International Conference on Web Information Systems Engineering
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In this paper we present StarNT, a dictionary-based fastlossless text transform algorithm. With a static generic dictionary, StarNT achieves a superior compression ratio thanalmost all the other recent efforts based on BWT and PPM.This algorithm utilizes ternary search tree to expedite transform encoding. Experimental results show that the average compression time has improved by orders of magnitudecompared with our previous algorithm LIPT and the additional time overhead it introduced to the backend compressor is unnoticeable.Based on StarNT, we propose StarZip, a domain-specificlossless text compression utility. Using domain-specificstatic dictionaries embedded in the system, StarZip achievesan average improvement in compression performance (interms of BPC) of 13% over bzip2 -9,19% over gzip -9, and10% over PPMD.