English

Practical Repetition-Aware Grammar Compression

Data Structures and Algorithms 2019-10-31 v1

Abstract

The goal of grammar compression is to construct a small sized context free grammar which uniquely generates the input text data. Among grammar compression methods, RePair is known for its good practical compression performance. MR-RePair was recently proposed as an improvement to RePair for constructing small-sized context free grammar for repetitive text data. However, a compact encoding scheme has not been discussed for MR-RePair. We propose a practical encoding method for MR-RePair and show its effectiveness through comparative experiments. Moreover, we extend MR-RePair to run-length context free grammar and design a novel variant for it called RL-MR-RePair. We experimentally demonstrate that a compression scheme consisting of RL-MR-RePair and the proposed encoding method show good performance on real repetitive datasets.

Keywords

Cite

@article{arxiv.1910.13479,
  title  = {Practical Repetition-Aware Grammar Compression},
  author = {Isamu Furuya},
  journal= {arXiv preprint arXiv:1910.13479},
  year   = {2019}
}
R2 v1 2026-06-23T11:58:47.104Z