A locally adaptive data compression scheme
Communications of the ACM
The general employee scheduling problem: an integration of MS and AI
Computers and Operations Research - Special issue: Applications of integer programming
An introduction to genetic algorithms
An introduction to genetic algorithms
Data compression via textual substitution
Journal of the ACM (JACM)
A Corpus for the Evaluation of Lossless Compression Algorithms
DCC '97 Proceedings of the Conference on Data Compression
Parsing Strategies for BWT Compression
DCC '01 Proceedings of the Data Compression Conference
Genetic programming: a paradigm for genetically breeding populations of computer programs to solve problems
Data Compression: The Complete Reference
Data Compression: The Complete Reference
Comparison of Text Models for BWT
DCC '07 Proceedings of the 2007 Data Compression Conference
IBM Journal of Research and Development
Generalized kraft inequality and arithmetic coding
IBM Journal of Research and Development
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Data compression is very important today and it will be even more important in the future. Textual data use only limited alphabet - total number of used symbols (letters, numbers, diacritics, dots, spaces, etc.). In most languages, letters are joined into syllables and words. Both these approaches has pros and cons, but none of them is the best for any file. This paper describes a variant of algorithm for evolving alphabet from characters and 2-grams, which is optimal for compressed text files. The efficiency of the new variant will be tested on three compression algorithms and a new compression algorithm based on LZ77 will be also used with this new approach.