HOLZ: High-Order Entropy Encoding of Lempel-Ziv Factor Distances
Data Structures and Algorithms
2021-11-05 v1
Abstract
We propose a new representation of the offsets of the Lempel-Ziv (LZ) factorization based on the co-lexicographic order of the processed prefixes. The selected offsets tend to approach the k-th order empirical entropy. Our evaluations show that this choice of offsets is superior to the rightmost LZ parsing and the bit-optimal LZ parsing on datasets with small high-order entropy.
Keywords
Cite
@article{arxiv.2111.02478,
title = {HOLZ: High-Order Entropy Encoding of Lempel-Ziv Factor Distances},
author = {Dominik Köppl and Gonzalo Navarro and Nicola Prezza},
journal= {arXiv preprint arXiv:2111.02478},
year = {2021}
}