Adding state merging to the DMC data compression algorithm - Young-Lai, Matthew (Information processing letters, 1999)
Dynamic Markov Compression (DMC) generates Markov models for data compression by starting with an initial model then expanding it one state at a time using a cloning operation. Typically, expansion continues until memory is full then the model is discarded and restarted. We present an alternative method that retracts the model based on selective merging of similar states. This requires extra time, but allows DMC to attain its best compression using much less memory.