Abstract
Information retrieval and data compression are the two main application areas where the rich theory of string algorithmics plays a fundamental role. In this paper, we consider one algorithmic problem from each of these areas and present highly efficient (linear or near linear time) algorithms for both problems. Our algorithms rely on augmenting the suffix tree, a fundamental data structure in string algorithmics. The augmentations are nontrivial and they form the technical crux of this paper. In particular, they consist of adding extra edges to suffix trees, resulting in Directed Acyclic Graphs (DAGs). Our algorithms construct these “suffix DAGs” and manipulate them to solve the two problems efficiently.
Partly supported by Alon Fellowship.
Partly supported by ESPRIT LTR Project no. 20244 - ALCOM IT.
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References
T. Bell, T. Cleary, and I. Witten. Text Compression. Academic Press, 1990.
G. S. Brodal. Finger search trees with constant insertion time. In ACM-SIAM Symposium on Discrete Algorithms, 1998.
M. Burrows and D. J. Wheeler. A block sorting lossless data compression algorithm. Technical Report 124, DEC SRC, 1994.
M. Crochemore and W. Rytter. Text Algorithms. Oxford Press, 1994.
J. G. Cleary and I. H. Witten. Data compression using adaptive coding and partial string matching. IEEE Transactions on Communications, 32(4):396–402, 1984.
D. M. Gusfield. Algorithms on Strings, Trees, and Sequences. Addison Wesley, 1998.
J. Hui. Color set size problem with applications to string matching. In Combinatorial Pattern Matching, 1992.
Y. Hershkovits and J. Ziv. On sliding window universal data compression with limited memory. In Information Theory symposium, pages 17–22, September 1995.
Y. Hershkovits and J. Ziv. On sliding window universal data compression with limited memory. IEEE Trans. on Information Theory, 44:66–78, January 1998.
E. M. McCreight. A space economical suffix tree construction algorithm. Journal of the ACM, 23(2):262–272, April 1976.
M. Rodeh, V. Pratt, and S. Even. Linear algorithm for data compression via string matching. Journal of the ACM, 28(1):16–24, January 1981.
B. Schieber and U. Vishkin. On finding lowest common ancestors:simplification and parallelization. SIAM Journal of Computing, 17:1253–1262, 1988.
T.A. Welch. A technique for high-performance data compression. IEEE Computer, pages 8–19, January 1984.
M. J. Weinberger, J. J. Rissanen, and M. Feder. A universal finite memory source. IEEE Transactions on Information Theory, 41(3):643–652, 1995.
H. Yokoo. An adaptive data compression method based on context sorting. In IEEE Data Compression Conference, 1996.
J. Ziv and A. Lempel. A universal algorithm for sequential data compression. IEEE Transactions on Information Theory, IT-23(3):337–343, May 1977.
J. Ziv and A. Lempel. Compression of individual sequences via variable-rate coding. IEEE Transactions on Information Theory, IT-24(5):530–536, September 1978.
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© 1998 Springer-Verlag Berlin Heidelberg
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Matias, Y., Muthukrishnan, S., Sahinalp, S.C., Ziv, J. (1998). Augmenting Suffix Trees, with Applications. In: Bilardi, G., Italiano, G.F., Pietracaprina, A., Pucci, G. (eds) Algorithms — ESA’ 98. ESA 1998. Lecture Notes in Computer Science, vol 1461. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-68530-8_6
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DOI: https://doi.org/10.1007/3-540-68530-8_6
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