A locally adaptive data compression scheme
Communications of the ACM
Bounds on the redundancy of Huffman codes
IEEE Transactions on Information Theory
Data compression using dynamic Markov modelling
The Computer Journal
Elements of information theory
Elements of information theory
Engineering the compression of massive tables: an experimental approach
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
An analysis of the Burrows—Wheeler transform
Journal of the ACM (JACM)
Improving table compression with combinatorial optimization
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
DCC '97 Proceedings of the Conference on Data Compression
Universal Lossless Source Coding with the Burrows Wheeler Transform
DCC '99 Proceedings of the Conference on Data Compression
On Optimality of Varients of the Block Sorting Compression
DCC '98 Proceedings of the Conference on Data Compression
Can We Do without Ranks in Burrows Wheeler Transform Compression?
DCC '01 Proceedings of the Data Compression Conference
When indexing equals compression: experiments with compressing suffix arrays and applications
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Compression boosting in optimal linear time using the Burrows-Wheeler Transform
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Succinct indexes for strings, binary relations and multilabeled trees
ACM Transactions on Algorithms (TALG)
Move-to-front, distance coding, and inversion frequencies revisited
CPM'07 Proceedings of the 18th annual conference on Combinatorial Pattern Matching
| Hi-index | 0.00 |
The Burrows-Wheeler transform [1] is one of the mainstays of lossless data compression. In most cases, its output is fed to Move to Front or other variations of symbol ranking compression. One of the main open problems [2] is to establish whether Move to Front, or more in general symbol ranking compression, is an essential part of the compression process. We settle this question positively by providing a new class of Burrows-Wheeler algorithms that use optimal partitions of strings, rather than symbol ranking, for the additional step. Our technique is a quite surprising specialization to strings of partitioning techniques devised by Buchsbaum et al. [3] for two-dimensional table compression. Following Manzini [4], we analyze two algorithms in the new class, in terms of the k-th order empirical entropy of a string and, for both algorithms, we obtain better compression guarantees than the ones reported in [4] for Burrows-Wheeler algorithms that use Move to Front.