2023/08/15 by Christina Boucher, Travis Gagie, Boucher, Christina +7 · 1 citation
Computer Science · #Algorithms and Data Compression #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Handwritten Text Recognition Techniques #Machine Learning and Algorithms
paper · pdf · doi:10.48550/arxiv.2308.07809
openalex publication_date 2023/08/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
A wavelet forest for a text T [1..n] over an alphabet σ takes n H0 (T) + o (n log σ) bits of space and supports access and rank on T in O (log σ) time. Kärkkäinen and Puglisi (2011) implicitly introduced wavelet forests and showed that when T is the Burrows-Wheeler Transform (BWT) of a string S, then a wavelet forest for T occupies space bounded in terms of higher-order empirical entropies of S even when the forest is implemented with uncompressed bitvectors. In this paper we show experimentally that wavelet forests also have better access locality than wavelet trees and are thus interesting even when higher-order compression is not effective on S, or when T is not a BWT at all.