Orthogonal Range Searching for Text Indexing

TL;DR

This paper surveys recent advances in using orthogonal range searching techniques, a concept from computational geometry, to improve text indexing methods for large and evolving textual data.

Contribution

It provides a comprehensive overview of how orthogonal range searching has been increasingly applied to text indexing, highlighting recent developments and deeper understanding.

Findings

Increased application of range searching in text indexing since the 90s

New data structures leveraging geometric methods for efficient queries

Enhanced understanding of geometric approaches in text data processing

Abstract

Text indexing, the problem in which one desires to preprocess a (usually large) text for future (shorter) queries, has been researched ever since the suffix tree was invented in the early 70's. With textual data continuing to increase and with changes in the way it is accessed, new data structures and new algorithmic methods are continuously required. Therefore, text indexing is of utmost importance and is a very active research domain. Orthogonal range searching, classically associated with the computational geometry community, is one of the tools that has increasingly become important for various text indexing applications. Initially, in the mid 90's there were a couple of results recognizing this connection. In the last few years we have seen an increase in use of this method and are reaching a deeper understanding of the range searching uses for text indexing. In this monograph we survey some of these results.