| 摘要 |
For context based compression techniques, for example Context Based YK compression, a method and system for grouping contexts from a given context model together to cre-ate a new context model that has fewer contexts, but retains ac-ceptable compression gains compared to the context model with more contexts is provided. According to an exemplary embodi-ment a set of files that are correlated to the file to be compressed (hereafter called training files) are read to determine, for an ini-tial context model, the empirical statistics of contexts and sym-bols. In some embodiments, this includes determining the esti-mated joint and conditional probabilities of the various contexts and symbols (or blocks of symbols). The initial context model is then reduced to a desired number of contexts, for example, by applying a grouping function g to the original set of contexts to obtain a new and smaller set of contexts. In some embodiments the step of applying a grouping function comprises iteratively grouping a pair of contexts together to form a grouped context, wherein each grouped context represents a local minimum based on the empirical statistics.
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