Improving PPM Algorithm Using Dictionaries

—We propose a method to improve traditional character-based PPM text compression algorithms. Consider a text file as a sequence of alternating words and non-words, the basic idea of our algorithm is to encode non-words and prefixes of words using character-based context models and encode suffixes of words using dictionary models. By using dictionary models, the algorithm can encode multiple characters as a whole, and thus enhance the compression efficiency. The advantages of the proposed algorithm are: 1) it does not require any text preprocessing; 2) it does not need any explicit codeword to identify switch between context and dictionary models; 3) it can be applied to any character-based PPM algorithms without incurring much additional computational cost. Test results show that significant improvements can be obtained over characterbased PPM, especially in low order cases. Keywords-Text compression; Markov model; PPM; Dictionary model.

• Type: Journal
• Year: 2011
• Where: DCC
• Authors: Yichuan Hu, Jianzhong (Charlie) Zhang, Farooq Khan, Ying Li
• Keywords: Algorithms, Character-based Ppm, Computer Graphics, DCC 2011, Dictionary Model