Bit-Level Affixation Text Compression Algorithms

Algorithmic data compression is a crucial concept in computer science aimed at reducing the size of stored data to minimize storage space. Particularly significant is the ability of an algorithm to compress data to the bit level, which greatly enhances the efficiency of storing vast amounts of data today. This paper introduces a novel approach to bit-level text compression algorithms, called BATCA. It features a distinctive dictionary design based on patterns of word construction, including vowel, prefix, suffix, and article formats, facilitating word referencing during both compression and decompression phases. Theoretical findings reveal significant compression achievements: a maximum bit compression per word of 69.79% with ASCII encoding, 84.89% with Unicode, and 92.45% with UTF -8, resulting in a maximum compression ratio of 16.55 times. Additionally, empirical evaluations on real data from the Calgary and ArTechnica corpora, compared against common applications, demonstrate the algorithm's ability to significantly outperform existing alternatives in terms of saved space percentage and compression ratios.