Efficient algorithms for on-line symbol ranking compression

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Abstract

Symbol ranking compression algorithms are known to achieve a very good compression ratio. Off-line symbol ranking algorithms (e.g., bzip, szip) are currently the state of the art for lossless data compression because of their excellent compression/time trade-off. Some on-line symbol ranking algorithms have been proposed in the past. They compress well but their slowness make them impractical. In this paper we design some fast on-line symbol ranking algorithms by fine tuning two data structures (skip lists and ternary trees) which are well known for their simplicity and efficiency.

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APA

Manzini, G. (1999). Efficient algorithms for on-line symbol ranking compression. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1643, pp. 277–288). Springer Verlag. https://doi.org/10.1007/3-540-48481-7_25

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