Faster and Simpler Online Computation of String Net Frequency

Fuente: arXiv
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Autore principale: Inenaga, Shunsuke
Natura: Preprint
Pubblicazione: 2024
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author Inenaga, Shunsuke
author_facet Inenaga, Shunsuke
contents An occurrence of a repeated substring $u$ in a string $S$ is called a net occurrence if extending the occurrence to the left or to the right decreases the number of occurrences to 1. The net frequency (NF) of a repeated substring $u$ in a string $S$ is the number of net occurrences of $u$ in $S$. Very recently, Guo et al. [SPIRE 2024] proposed an online $O(n \log σ)$-time algorithm that maintains a data structure of $O(n)$ space which answers Single-NF queries in $O(m\log σ+ σ^2)$ time and reports all answers of the All-NF problem in $O(nσ^2)$ time. Here, $n$ is the length of the input string $S$, $m$ is the query pattern length, and $σ$ is the alphabet size. The $σ^2$ term is a major drawback of their method since computing string net frequencies is originally motivated for Chinese language processing where $σ$ can be thousands large. This paper presents an improved online $O(n \log σ)$-time algorithm, which answers Single-NF queries in $O(m \log σ)$ time and reports all answers to the All-NF problem in output-optimal $O(|\mathsf{NF}^+(S)|)$ time, where $\mathsf{NF}^+(S)$ is the set of substrings of $S$ paired with their positive NF values. We note that $|\mathsf{NF}^+(S)| = O(n)$ always holds. In contract to Guo et al.'s algorithm that is based on Ukkonen's suffix tree construction, our algorithm is based on Weiner's suffix tree construction.
format Preprint
id arxiv_https___arxiv_org_abs_2410_06837
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Faster and Simpler Online Computation of String Net Frequency
Inenaga, Shunsuke
Data Structures and Algorithms
An occurrence of a repeated substring $u$ in a string $S$ is called a net occurrence if extending the occurrence to the left or to the right decreases the number of occurrences to 1. The net frequency (NF) of a repeated substring $u$ in a string $S$ is the number of net occurrences of $u$ in $S$. Very recently, Guo et al. [SPIRE 2024] proposed an online $O(n \log σ)$-time algorithm that maintains a data structure of $O(n)$ space which answers Single-NF queries in $O(m\log σ+ σ^2)$ time and reports all answers of the All-NF problem in $O(nσ^2)$ time. Here, $n$ is the length of the input string $S$, $m$ is the query pattern length, and $σ$ is the alphabet size. The $σ^2$ term is a major drawback of their method since computing string net frequencies is originally motivated for Chinese language processing where $σ$ can be thousands large. This paper presents an improved online $O(n \log σ)$-time algorithm, which answers Single-NF queries in $O(m \log σ)$ time and reports all answers to the All-NF problem in output-optimal $O(|\mathsf{NF}^+(S)|)$ time, where $\mathsf{NF}^+(S)$ is the set of substrings of $S$ paired with their positive NF values. We note that $|\mathsf{NF}^+(S)| = O(n)$ always holds. In contract to Guo et al.'s algorithm that is based on Ukkonen's suffix tree construction, our algorithm is based on Weiner's suffix tree construction.
title Faster and Simpler Online Computation of String Net Frequency
topic Data Structures and Algorithms
url https://arxiv.org/abs/2410.06837