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Efficient Algorithms for On-Line Symbol Ranking Compression

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Algorithms - ESA’ 99 (ESA 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1643))

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Abstract

Symbol ranking compression algorithms are known to achieve a very good compression ratio. Off-line symbol ranking algorithms (e.g., bzip, szip) are currently the state of the art for lossless data compression because of their excellent compression/time trade-off.

Some on-line symbol ranking algorithms have been proposed in the past. They compress well but their slowness make them impractical. In this paper we design some fast on-line symbol ranking algorithms by fine tuning two data structures (skip lists and ternary trees) which are well known for their simplicity and efficiency.

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References

  1. R. Arnold and T. Bell. The Canterbury corpus home page. http://corpus.canterbury.ac.nz.

  2. J. Bentley and R. Sedgewick. Fast algorithms for sorting and searching strings. In Proceedings of the Eighth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 360–369, New Orleans, Louisiana, 1997.

    Google Scholar 

  3. J. Bentley, D. Sleator, R. Tarjan, and V. Wei. A locally adaptive data compression scheme. Communications of the ACM, 29(4):320–330, April 1986.

    Article  MATH  MathSciNet  Google Scholar 

  4. J. R. Bitner. Heuristics that dynamically organize data structures. SIAM J. Comput., 8(1):82–110, 1979.

    Article  MATH  MathSciNet  Google Scholar 

  5. M. Burrows and D. J. Wheeler. Ablock sorting lossless data compression algorithm. Technical Report 124, Digital Equipment Corporation, Palo Alto, California, 1994.

    Google Scholar 

  6. J. G. Cleary and W. J. Teahan. Unbounded length contexts for PPM. The Computer Journal, 40(2/3):67–75, 1997.

    Article  Google Scholar 

  7. J. G. Cleary and I. H. Witten. Data compression using adaptive coding and partial string matching. IEEE Transactions on Communications, COM-32:306–315, 1984.

    MathSciNet  Google Scholar 

  8. P. Fenwick. The Burrows-Wheeler transform for block sorting text compression: principles and improvements. The Computer Journal, 39(9):731–740, 1996.

    Article  Google Scholar 

  9. P. Fenwick. Symbol ranking text compression with Shannon recoding. J. UCS, 3(2):70–85, 1997.

    MATH  Google Scholar 

  10. P. Howard and J. Vitter. Design and analysis of fast text compression based on quasi-arithmetic coding. In DCC: Data Compression Conference. IEEE Computer Society TCC, 1993.

    Google Scholar 

  11. W. Pugh. Skip lists: A probabilistic alternative to balanced trees. Communications of the ACM, 33(6):668–676, June 1990.

    Article  MathSciNet  Google Scholar 

  12. K. Sadakane. Text compression using recency rank with context and relation to context sorting, block sorting and PPM*. In Proc. Int. Conference on Compression and Complexity of Sequences (SEQUENCES’ 97). IEEE Computer Society TCC, 1997.

    Google Scholar 

  13. D. Salomon. Data Compression: the Complete Reference. Springer Verlag, 1997.

    Google Scholar 

  14. M. Schindler. A fast block-sorting algorithm for lossless data compression. In Data Compression Conference. IEEE Computer Society TCC, 1997. http://eiunix.tuwien.ac.at/~michael/st/.

  15. M. Schindler. The szip home page, 1997. http://www.compressconsult.com/szip/.

  16. R. Sedgewick. Algorithms in C. Addison-Wesley, Reading, MA, USA, 3rd edition, 1997.

    MATH  Google Scholar 

  17. J. Seward. The bzip2 home page, 1997. http://www.digistar.com/bzip2/index.html.

  18. J. Vitter. Design and analysis of dynamic Huffman codes. Journal of theACM, 34(4):825–845, October 1987.

    MATH  MathSciNet  Google Scholar 

  19. I. Witten, R. Neal, and J. Cleary. Arithmetic coding for data compression. Communications of the ACM, 30(6):520–540, June 1987.

    Article  Google Scholar 

  20. H. Yokoo. Data compression using a sort-based similarity measure. The Computer Journal, 40(2/3):94–102, 1997.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Dipartimento di Scienze e Tecnologie Avanzate, Università del Piemonte Orientale “Amedeo Avogadro”, I-15100, Alessandria, Italy

    Giovanni Manzini

  2. Istituto di Matematica Computazionale, CNR, I-56126, Pisa, Italy

    Giovanni Manzini

Authors
  1. Giovanni Manzini
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Editor information

Editors and Affiliations

  1. Department of Applied Mathematics and DIMATIA Centre, Charles University, Malostranská nám. 25, CZ-11800, Prague 1, Czech Republic

    Jaroslav Nešetřil

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© 1999 Springer-Verlag Berlin Heidelberg

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Manzini, G. (1999). Efficient Algorithms for On-Line Symbol Ranking Compression. In: Nešetřil, J. (eds) Algorithms - ESA’ 99. ESA 1999. Lecture Notes in Computer Science, vol 1643. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48481-7_25

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  • DOI: https://doi.org/10.1007/3-540-48481-7_25

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66251-8

  • Online ISBN: 978-3-540-48481-3

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