Skip to main content

LRM-Trees: Compressed Indices, Adaptive Sorting, and Compressed Permutations

  • Conference paper
Combinatorial Pattern Matching (CPM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6661))

Included in the following conference series:

  • 1061 Accesses

Abstract

LRM-Trees are an elegant way to partition a sequence of values into sorted consecutive blocks, and to express the relative position of the first element of each block within a previous block. They were used to encode ordinal trees and to index integer arrays in order to support range minimum queries on them. We describe how they yield many other convenient results in a variety of areas: compressed succinct indices for range minimum queries on partially sorted arrays; a new adaptive sorting algorithm; and a compressed succinct data structure for permutations supporting direct and inverse application in time inversely proportional to the permutation’s compressibility.

First and third author partially funded by Fondecyt grant 1-110066, Chile; second author supported by a DFG grant (German Research Foundation).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Barbay, J., He, M., Munro, J.I., Rao, S.S.: Succinct indexes for strings, binary relations, and multi-labeled trees. In: Proc. SODA, pp. 680–689. ACM/SIAM (2007)

    Google Scholar 

  2. Barbay, J., Navarro, G.: Compressed representations of permutations, and applications. In: Proc. STACS, pp. 111–122. IBFI Schloss Dagstuhl (2009)

    Google Scholar 

  3. Bender, M.A., Farach-Colton, M., Pemmasani, G., Skiena, S., Sumazin, P.: Lowest common ancestors in trees and directed acyclic graphs. J. Algorithms 57(2), 75–94 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  4. Benoit, D., Demaine, E.D., Munro, J.I., Raman, R., Raman, V., Rao, S.S.: Representing trees of higher degree. Algorithmica 43(4), 275–292 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  5. Brodal, G.S., Davoodi, P., Rao, S.S.: On space efficient two dimensional range minimum data structures. In: de Berg, M., Meyer, U. (eds.) ESA 2010. LNCS, vol. 6347, pp. 171–182. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  6. Chen, K.-Y., Chao, K.-M.: On the range maximum-sum segment query problem. In: Fleischer, R., Trippen, G. (eds.) ISAAC 2004. LNCS, vol. 3341, pp. 294–305. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  7. Crochemore, M., Iliopoulos, C.S., Kubica, M., Rahman, M.S., Walen, T.: Improved algorithms for the range next value problem and applications. In: Proc. STACS, pp. 205–216. IBFI Schloss Dagstuhl (2008)

    Google Scholar 

  8. Daskalakis, C., Karp, R.M., Mossel, E., Riesenfeld, S., Verbin, E.: Sorting and selection in posets. In: Proc. SODA, pp. 392–401. ACM/SIAM (2009)

    Google Scholar 

  9. Fischer, J.: Optimal succinctness for range minimum queries. In: López-Ortiz, A. (ed.) LATIN 2010. LNCS, vol. 6034, pp. 158–169. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  10. Fischer, J., Heun, V., Stühler, H.M.: Practical entropy bounded schemes for O(1)-range minimum queries. In: Proc. DCC, pp. 272–281. IEEE Press, Los Alamitos (2008)

    Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  12. Gál, A., Miltersen, P.B.: The cell probe complexity of succinct data structures. Theor. Comput. Sci. 379(3), 405–417 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  13. Golynski, A.: Optimal lower bounds for rank and select indexes. Theor. Comput. Sci. 387(3), 348–359 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  14. Grossi, R., Gupta, A., Vitter, J.S.: High-order entropy-compressed text indexes. In: Proc. SODA, pp. 841–850. ACM/SIAM (2003)

    Google Scholar 

  15. Huffman, D.: A method for the construction of minimum-redundancy codes. Proceedings of the I.R.E. 40, 1090–1101 (1952)

    Article  MATH  Google Scholar 

  16. Jacobson, G.: Space-efficient static trees and graphs. In: Proc. FOCS, pp. 549–554. IEEE Computer Society, Los Alamitos (1989)

    Google Scholar 

  17. Jansson, J., Sadakane, K., Sung, W.-K.: Ultra-succinct representation of ordered trees. In: Proc. SODA, pp. 575–584. ACM/SIAM (2007)

    Google Scholar 

  18. Knuth, D.E.: Art of Computer Programming, 2nd edn. Sorting and Searching, vol. 3. Addison-Wesley Professional, Reading (1998)

    MATH  Google Scholar 

  19. Levcopoulos, C., Petersson, O.: Sorting shuffled monotone sequences. Inf. Comput. 112(1), 37–50 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  20. Mäkinen, V., Navarro, G.: Implicit compression boosting with applications to self-indexing. In: Ziviani, N., Baeza-Yates, R. (eds.) SPIRE 2007. LNCS, vol. 4726, pp. 229–241. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  21. Munro, J.I., Raman, R., Raman, V., Rao, S.S.: Succinct representations of permutations. In: Baeten, J.C.M., Lenstra, J.K., Parrow, J., Woeginger, G.J. (eds.) ICALP 2003. LNCS, vol. 2719, pp. 345–356. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  22. Navarro, G., Mäkinen, V.: Compressed full-text indexes. ACM Computing Surveys 39(1), Article No. 2 (2007)

    Google Scholar 

  23. Pǎtraşcu, M.: Succincter. In: Proc. FOCS, pp. 305–313. IEEE Computer Society, Los Alamitos (2008)

    Google Scholar 

  24. Raman, R., Raman, V., Rao, S.S.: Succinct indexable dictionaries with applications to encoding k-ary trees and multisets. ACM Transactions on Algorithms 3(4), Art. 43 (2007)

    Google Scholar 

  25. Sadakane, K., Grossi, R.: Squeezing succinct data structures into entropy bounds. In: Proc. SODA, pp. 1230–1239. ACM/SIAM (2006)

    Google Scholar 

  26. Sadakane, K., Navarro, G.: Fully-functional succinct trees. In: Proc. SODA, pp. 134–149. ACM/SIAM (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Barbay, J., Fischer, J., Navarro, G. (2011). LRM-Trees: Compressed Indices, Adaptive Sorting, and Compressed Permutations. In: Giancarlo, R., Manzini, G. (eds) Combinatorial Pattern Matching. CPM 2011. Lecture Notes in Computer Science, vol 6661. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21458-5_25

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-21458-5_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21457-8

  • Online ISBN: 978-3-642-21458-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics