Abstract
One of the most successful natural language compression methods is word-based Huffman. However, such a two-pass semi-static compressor is not well suited to many interesting real-time transmission scenarios. A one-pass adaptive variant of Huffman exists, but it is character-oriented and rather complex. In this paper we implement word-based adaptive Huffman compression, showing that it obtains very competitive compression ratios. Then, we show how End-Tagged Dense Code, an alternative to word-based Huffman, can be turned into a faster and much simpler adaptive compression method which obtains almost the same compression ratios.
This word is partially supported by CYTED VII.19 RIBIDI Project. It is also funded in part (for the Spanish group) by MCyT (PGE and FEDER) grant(TIC2003-06593) and (for the third author) by Millennium Nucleus Center for Web Research, Grant (P01-029-F), Mideplan, Chile.
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Brisaboa, N.R., Fariña, A., Navarro, G., Paramá, J.R. (2004). Simple, Fast, and Efficient Natural Language Adaptive Compression. In: Apostolico, A., Melucci, M. (eds) String Processing and Information Retrieval. SPIRE 2004. Lecture Notes in Computer Science, vol 3246. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30213-1_34
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DOI: https://doi.org/10.1007/978-3-540-30213-1_34
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