HOLZ: High-Order Entropy Encoding of Lempel-Ziv Factor Distances
Abstract
We propose a new representation of the offsets of the Lempel-Ziv (LZ) factorization based on the co-lexicographic order of the text's prefixes. The selected offsets tend to approach the k-th order empirical entropy. Our evaluations show that this choice is superior to the rightmost and bit-optimal LZ parsings on datasets with small high-order entropy.
Más información
| Título según WOS: | HOLZ: High-Order Entropy Encoding of Lempel-Ziv Factor Distances |
| Título de la Revista: | 2020 DATA COMPRESSION CONFERENCE (DCC 2020) |
| Editorial: | IEEE COMPUTER SOC |
| Fecha de publicación: | 2022 |
| Página de inicio: | 83 |
| Página final: | 92 |
| DOI: |
10.1109/DCC52660.2022.00016 |
| Notas: | ISI |