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ABSTRACT
A data compression scheme that exploits locality of reference, such as occurs when words are used frequently over short intervals and then fall into long periods of disuse, is described. The scheme is based on a simple heuristic for self-organizing sequential search and on variable-length encodings of integers. We prove that it never performs much worse than Huffman coding and can perform substantially better; experiments on real files show that its performance is usually quite close to that of Huffman coding. Our scheme has many implementation advantages: it is simple, allows fast encoding and decoding, and requires only one pass over the data to be compressed (static Huffman coding takes two passes).
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 60
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Dennis Grinberg , Sivaramakrishnan Rajagopalan , Ramarathnam Venkatesan , Victor K. Wei, Splay trees for data compression, Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms, p.522-530, January 22-24, 1995, San Francisco, California, United States
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Edleno Silva de Moura , Gonzalo Navarro , Nivio Ziviani , Ricardo Baeza-Yates, Fast searching on compressed text allowing errors, Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval, p.298-306, August 24-28, 1998, Melbourne, Australia
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REVIEW
"R. Nigel Horspool : Reviewer"
If a typical text file in a computer system is decomposed into words (sequences
of alphanumeric characters) separated by punctuation characters, we would
normally find that the same words occur repeatedly. Furthermore, words tend to
exhibit
more...
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