Clustering words
S\'ebastien Ferenczi, Luca Q. Zamboni
TL;DR
This paper characterizes words that cluster under the Burrows-Wheeler transform by linking them to interval exchange transformations and provides examples of such clustering words.
Contribution
It introduces a novel characterization of clustering words using interval exchange transformations and constructs explicit examples.
Findings
Words clustering under BWT correspond to interval exchange trajectories.
Examples of clustering words are explicitly constructed.
Theoretical link between BWT clustering and dynamical systems.
Abstract
We characterize words which cluster under the Burrows-Wheeler transform as those words such that occurs in a trajectory of an interval exchange transformation, and build examples of clustering words.
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Taxonomy
TopicsMathematical Dynamics and Fractals · Music and Audio Processing · Neural Networks and Applications