A Comparative Review of Lossless Text Compression Algorithms: From Classic Techniques to Hybrid Models
BPC; Compression; Compression Rate; Huffman; Shannon-Fano
The lossless text compression is an essential part of data transmission and storage that allows using resources effectively without losing data integrity. This paper combines the most recent research with the important discoveries of benchmark research that focuses on essential algorithms such as Huffman LZW and Shannon-Fano and advanced hybrid algorithms such as LZW and Burrows-Wheeler Transform (BWT -based algorithms. The trade-offs between compression ratio, speed and adaptability can be observed comparing how algorithmic concepts, operational stages and empirical performance evolve in different datasets. This evaluation ends with recommendations on how to choose algorithms as well as future research recommendations. 2025 IEEE.
Sharma, Mahesh Kumar; Alapatt, Bosco Paul; Sharma, Vandana; Shanbhog, Manjula
2025 2nd International Conference on Advanced Computing and Emerging Technologies, ACET 2025;
Institute of Electrical and Electronics Engineers Inc.
Restricted Access; Hardcopy may be available in the library
https://doi.org/10.1109/ACET67282.2025.11430241 https://www.scopus.com/pages/publications/105037939371?origin=resultslist
Sharma M.K., Christ University, Uttar Pradesh, Ghaziabad, India; Alapatt B.P., Christ University, Bengaluru, India; Sharma V., Christ University, Bengaluru, India; Shanbhog M., Christ University, Bengaluru, India