A compressed dynamic self-index for highly repetitive text collections
Data Structures and Algorithms
2018-04-25 v4
Abstract
We present a novel compressed dynamic self-index for highly repetitive text collections. Signature encoding is a compressed dynamic self-index for highly repetitive texts and has a large disadvantage that the pattern search for short patterns is slow. We improve this disadvantage for faster pattern search by leveraging an idea behind truncated suffix tree and present the first compressed dynamic self-index named TST-index that supports not only fast pattern search but also dynamic update operation of index for highly repetitive texts. Experiments using a benchmark dataset of highly repetitive texts show that the pattern search of TST-index is significantly improved.
Keywords
Cite
@article{arxiv.1711.02855,
title = {A compressed dynamic self-index for highly repetitive text collections},
author = {Takaaki Nishimoto and Yoshimasa Takabatake and Yasuo Tabei},
journal= {arXiv preprint arXiv:1711.02855},
year = {2018}
}