Title
List Update Algorithms for Data 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 showMTF 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. [LATIN 2008]. 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
2008
10.1109/DCC.2008.25
DCC
Keywords
Field
DocType
compression algorithm,bwt compression,various list update algorithm,burrows-wheeler compression,bwt-based compression,compression mechanism,list update algorithms,reference model,compression schema,good list update algorithm,data compression,list update algorithm,computer science,burrows wheeler transform,competitive analysis,algorithms,frequency,encoding,text analysis,transpose,timestamp,sorting,predictive models,informatics
Locality of reference,List update problem,Burrows–Wheeler transform,Transpose,Computer science,Algorithm,Calgary corpus,Theoretical computer science,Timestamp,Data compression,Competitive analysis
Conference
Citations 
PageRank 
References 
1
0.36
2
Authors
3
Name
Order
Citations
PageRank
Reza Dorrigiv117614.02
Alejandro López-Ortiz21252107.44
J. Ian Munro33010462.97