Paper Info
Title
An Application of Self-organizing Data Structures to Compression
Abstract
List update algorithms have been widely used as subroutines in compression schemas, most notably as part of Burrows-Wheeler compression. The Burrows-Wheeler transform (BWT), which is the basis of many state-of-the-art general purpose compressors applies a compression algorithm to a permuted version of the original text. List update algorithms are a common choice for this second stage of BWT-based compression. In this paper we perform an experimental comparison of various list update algorithms both as stand alone compression mechanisms and as a second stage of the BWT-based compression. Our experiments show MTF outperforms other list update algorithms in practice after BWT. This is consistent with the intuition that BWT increases locality of reference and the predicted result from the locality of reference model of Angelopoulos et al. [1]. Lastly, we observe that due to an often neglected difference in the cost models, good list update algorithms may be far from optimal for BWT compression and construct an explicit example of this phenomena. This is a fact that had yet to be supported theoretically in the literature.
Year
DOI
Venue
2009
10.1007/978-3-642-02011-7_14
SEA
Keywords
Field
DocType
compression algorithm,bwt compression,self-organizing data structures,various list update algorithm,burrows-wheeler compression,bwt-based compression,compression mechanism,reference model,compression schema,good list update algorithm,list update algorithm,burrows wheeler transform,self organization,data structure
Data structure,Online algorithm,Locality of reference,List update problem,Computer science,Algorithm,Theoretical computer science,Compression ratio,Data compression,Lossless compression,Competitive analysis
Conference
Volume
ISSN
Citations 
5526
0302-9743
5
PageRank 
References 
Authors
0.47
19
3
Name
Order
Citations
PageRank
Reza Dorrigiv117614.02
Alejandro López-Ortiz21252107.44
J. Ian Munro33010462.97