Fast Multiple Order-Preserving Matching Algorithms

TL;DR

This paper introduces two new algorithms for multiple order-preserving matching that significantly improve speed, with one achieving sublinear average time and the other linear average time, advancing the efficiency of pattern matching tasks.

Contribution

The paper presents two novel algorithms for multiple order-preserving matching, achieving faster average-case performance than existing methods.

Findings

One algorithm runs in sublinear average time.

The other algorithm runs in linear average time.

Both algorithms outperform previous methods in speed.

Abstract

Given a text $T$ and a pattern $P$, the order-preserving matching problem is to find all substrings in $T$ which have the same relative orders as $P$. Order-preserving matching has been an active research area since it was introduced by Kubica et al. \cite{kubica2013linear} and Kim et al. \cite{kim2014order}. In this paper we present two algorithms for the multiple order-preserving matching problem, one of which runs in sublinear time on average and the other in linear time on average. Both algorithms run much faster than the previous algorithms.