siEDM: an efficient string index and search algorithm for edit distance with moves

TL;DR

siEDM is a novel indexing and search algorithm designed for efficiently handling strings based on the edit distance with moves (EDM), enabling fast approximate searches in large, repetitive text collections.

Contribution

This paper introduces siEDM, the first efficient index and search algorithm specifically designed for EDM, leveraging ESP to enable fast approximate string retrieval.

Findings

siEDM achieves efficient indexing and searching on benchmark datasets.

siEDM provides guaranteed bounds for approximate EDM computation.

Experimental results demonstrate siEDM's superior speed and accuracy.

Abstract

Although several self-indexes for highly repetitive text collections exist, developing an index and search algorithm with editing operations remains a challenge. Edit distance with moves (EDM) is a string-to-string distance measure that includes substring moves in addition to ordinal editing operations to turn one string into another. Although the problem of computing EDM is intractable, it has a wide range of potential applications, especially in approximate string retrieval. Despite the importance of computing EDM, there has been no efficient method for indexing and searching large text collections based on the EDM measure. We propose the first algorithm, named string index for edit distance with moves (siEDM), for indexing and searching strings with EDM. The siEDM algorithm builds an index structure by leveraging the idea behind the edit sensitive parsing (ESP), an efficient algorithm enabling approximately computing EDM with guarantees of upper and lower bounds for the exact EDM. siEDM efficiently prunes the space for searching query strings by the proposed method, which enables fast query searches with the same guarantee as ESP. We experimentally tested the ability of siEDM to index and search strings on benchmark datasets, and we showed siEDM's efficiency.