Compact multi-text index for circular Cartesian tree matching

2026-06-17

AI Summary

This study addresses the lack of systematic empirical evaluation of practical indexing structures for Cartesian tree matching (CTM), particularly on sequence data exhibiting natural variability. It presents the first practical implementation of an index based on the Cartesian-augmented Burrows–Wheeler Transform (ceBWT), supporting both dynamically extensible and statically compressed variants, and introduces a compact multi-text index structure. The proposed approach significantly improves space efficiency and query performance while preserving exact structural matching capabilities, thereby effectively bridging the gap between CTM theory and real-world applications.

Abstract

Cartesian tree matching (CTM) is a structural pattern matching approach that identifies sequences with the same Cartesian tree topology, making it suitable for data with natural variability where exact comparisons carry little semantic meaning. While theoretical algorithms for CTM have been studied extensively, systematic empirical evaluations of practical implementations remain rare. This article presents an implementation of the Cartesian Extended Burrows-Wheeler Transform (ceBWT), a BWT-based index structure for CTM. The implementation supports both a dynamically extendable and a statically compressed index variant.

Problem

• Cartesian tree matching
• index structure
• empirical evaluation
• Burrows-Wheeler Transform

Innovation

• Cartesian tree matching
• ceBWT
• Burrows-Wheeler Transform
• compressed index
• dynamic index