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Compressed Suffix Trees

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  • First Online:
Encyclopedia of Algorithms
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Years and Authors of Summarized Original Work

  • 2007; Sadakane

  • 2009; Fischer, Mäkinen, Navarro

  • 2010; Ohlebusch, Fischer, Gog

  • 2011; Russo, Navarro, Oliveira

Problem Definition

The problem consists in representing suffix trees in main memory. The representation needs to support operations efficiently, using a reasonable amount of space.

Suffix trees were proposed by Weiner in 1973 [16]. Donald Knuth called them the “Algorithm of the Year.” Their ubiquitous nature was quickly perceived and used to solve a myriad of string processing problems. The downside of this flexibility was the notorious amount of space necessary to keep it in main memory. A direct implementation is several times larger than the file it is indexing. Initial research into this matter discovered smaller data structures, sometimes by sacrificing functionality, namely, suffix arrays [6], directed acyclic word graphs [5], or engineered solutions.

Compressed Suffix Trees, Fig. 1
figure 327 figure 327

Suffix tree of string abbbab, with the leaves...

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Recommended Reading

  1. Abeliuk A, Cánovas R, Navarro G (2013) Practical compressed suffix trees. Algorithms 6(2):319–351

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  2. Abouelhoda MI, Kurtz S, Ohlebusch E (2004) Replacing suffix trees with enhanced suffix arrays. J Discr Algorithms 2(1):53–86

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  3. Fischer J (2010) Wee LCP. Inf Process Lett 110(8–9):317–320

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  4. Fischer J, Mäkinen V, Navarro G (2009) Faster entropy-bounded compressed suffix trees. Theor Comput Sci 410(51):5354–5364

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  5. Gusfield D (1997) Algorithms on strings, trees and sequences computer science and computational biology. Cambridge University Press, Cambridge/New York

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  6. Manber U, Myers G (1993) Suffix arrays: a new method for on-line string searches. SIAM J Comput 22(5):935–948

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  7. Navarro G, Mäkinen V (2007) Compressed full-text indexes. ACM Comput Surv 39(1): article 2

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  8. Navarro G, Ordóñez A (2014) Faster compressed suffix trees for repetitive text collections. In: Proceedings of the 13th international symposium on experimental algorithms (SEA), Copenhagen. LNCS 8504, pp 424–435

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  9. Navarro G, Russo L (2014) Fast fully-compressed suffix trees. In: Proceedings of the 24th data compression conference (DCC), Snowbird, pp 283–291

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  10. Navarro G, Sadakane K (2014) Fully-functional static and dynamic succinct trees. ACM Trans Algorithms 10(3):article 16

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  11. Ohlebusch E, Gog S (2009) A compressed enhanced suffix array supporting fast string matching. In: String processing and information retrieval, Saariselkä. Springer, pp 51–62

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  12. Ohlebusch E, Fischer J, Gog S (2010) CST++. In: String processing and information retrieval, Los Cabos. Springer, pp 322–333

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  13. Russo L, Navarro G, Oliveira A (2011) Fully-compressed suffix trees. ACM Trans Algorithms (TALG) 7(4):article 53, 35p

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  14. Sadakane K (2007) Compressed suffix trees with full functionality. Theory Comput Syst 41(4):589–607

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  15. Välimäki N, Gerlach W, Dixit K, Mäkinen V (2007) Engineering a compressed suffix tree implementation. In: Experimental algorithms, Rome. Springer, pp 217–228

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  16. Weiner P (1973) Linear pattern matching algorithms. In: IEEE conference record of 14th annual symposium on switching and automata theory, 1973. SWAT’08. IEEE, pp 1–11. http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=4569717

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Correspondence to Luís M. S. Russo .

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Russo, L.M.S. (2016). Compressed Suffix Trees. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2864-4_643

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