Optimally Computing Compressed Indexing Arrays Based on the Compact Directed Acyclic Word Graph
Abstract
In this paper, we present the first study of the computational complexity of converting an automata-based text index structure, called the Compact Directed Acyclic Word Graph (CDAWG), of size for a text of length into other text indexing structures for the same text, suitable for highly repetitive texts: the run-length BWT of size , the irreducible PLCP array of size , and the quasi-irreducible LPF array of size , as well as the lex-parse of size and the LZ77-parse of size , where . As main results, we showed that the above structures can be optimally computed from either the CDAWG for stored in read-only memory or its self-index version of size without a text in worst-case time and words of working space. To obtain the above results, we devised techniques for enumerating a particular subset of suffixes in the lexicographic and text orders using the forward and backward search on the CDAWG by extending the results by Belazzougui et al. in 2015.
Cite
@article{arxiv.2308.02269,
title = {Optimally Computing Compressed Indexing Arrays Based on the Compact Directed Acyclic Word Graph},
author = {Hiroki Arimura and Shunsuke Inenaga and Yasuaki Kobayashi and Yuto Nakashima and Mizuki Sue},
journal= {arXiv preprint arXiv:2308.02269},
year = {2023}
}
Comments
The short version of this paper will appear in SPIRE 2023, Pisa, Italy, September 26-28, 2023, Lecture Notes in Computer Science, Springer