Weighted Burrows-Wheeler Compression

TL;DR

This paper explores a novel compression method combining weighted encoding with the Burrows-Wheeler Transform, showing improved efficiency for skewed data distributions through empirical evaluation.

Contribution

It introduces a weighted compression approach applied to Burrows-Wheeler transformed files, demonstrating its effectiveness in handling skewed data distributions.

Findings

Enhanced compression efficiency for skewed data

Empirical validation of the weighted BWT method

Improved encoding performance over traditional methods

Abstract

A weight based dynamic compression method has recently been proposed, which is especially suitable for the encoding of files with locally skewed distributions. Its main idea is to assign larger weights to closer to be encoded symbols by means of an increasing weight function, rather than considering each position in the text evenly. A well known transformation that tends to convert input files into files with a more skewed distribution is the Burrows-Wheeler Transform. This paper employs the weighted approach on Burrows-Wheeler transformed files and provides empirical evidence of the efficiency of this combination.