Skip to main content

On the Range Maximum-Sum Segment Query Problem

  • Conference paper
Algorithms and Computation (ISAAC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3341))

Included in the following conference series:

Abstract

We are given a sequence A of n real numbers which is to be preprocessed. In the Range Maximum-Sum Segment Query (RMSQ) problem, a query is comprised of two intervals [i,j] and [k,l] and our goal is to return the maximum-sum segment of A whose starting index lies in [i,j] and ending index lies in [k,l]. We propose the first known algorithm for this problem in O(n) preprocessing time and O(1) time per query under the unit-cost RAM model. We also use the RMSQ techniques to solve three relevant problems in linear time. These variations on the basic theme demonstrate the utilities of the techniques developed in this paper.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

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. Bender, M.A., Farach-Colton, M.: The LCA Problem Revisited. In: Proceedings of the 4th Latin American Symposium on Theoretical Informatics, vol. 17, pp. 88–94 (2000)

    Google Scholar 

  2. Bentley, J.: Programming Pearls - Algorithm Design Techniques. In: CACM, pp. 865–871 (1984)

    Google Scholar 

  3. Chung, K., Lu, H.-I.: An optimal algorithm for the maximum-density segment problem. In: Di Battista, G., Zwick, U. (eds.) ESA 2003. LNCS, vol. 2832, pp. 136–147. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  4. Fan, T.-H., Lee, S., Lu, H.-I., Tsou, T.-S., Wang, T.-C., Yao, A.: An optimal algorithm for maximum-sum segment and its application in bioinformatics extended abstract. In: Ibarra, O.H., Dang, Z. (eds.) CIAA 2003. LNCS, vol. 2759, pp. 251–257. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  5. Gabow, H., Bentley, J., Tarjan, R.:Scaling and Related Techniques for Geometry Problems. In: Proc. Symp Theory of Computing(STOC), pp. 135–143 (1984)

    Google Scholar 

  6. Gusfield, D.: Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology. Cambridge University Press, Cambridge (1999)

    Google Scholar 

  7. Harel, D., Tarjan, R.E.: Fast Algorithms for Finding Nearest Common Ancestors. SIAM J Comput. 13, 338–355 (1984)

    Article  MATH  MathSciNet  Google Scholar 

  8. Huang, X.: An Algorithm for Identifying Regions of a DNA Sequence that Satisfy a Content Requirement. CABIOS 10, 219–225 (1994)

    Google Scholar 

  9. Lin, Y.-L., Huang, X., Jiang, T., Chao, K.-M.: MAVG: Locating Non-Overlapping Maximum Average Segments in a Given Sequence. Bioinformatics 19, 151–152 (2003)

    Article  Google Scholar 

  10. Lin, Y.-L., Jiang, T., Chao, K.-M.: Efficient Algorithms for Locating the Length-constrained Heaviest Segments with Applications to Biomolecular Sequence Analysis. Journal of Computer and System Sciences 65, 570–586 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  11. Ruzzo, W.L., Tompa, M.: A Linear Time Algorithm for Finding All Maximal Scoring Subsequences. In: 7th Intl. Conf. Intelligent Systems for Molecular Biology, Heidelberg, Germany, pp. 234–241 (1999)

    Google Scholar 

  12. Schieber, B., Vishkin, U.: On Finding Lowest Common Ancestors: Simplification and Parallelization. SIAM J. Comput. 17, 1253–1262 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  13. Vuillemin, J.: A Unifying Look at Data Structures. CACM 23, 229–239 (1980)

    MATH  MathSciNet  Google Scholar 

  14. Wang, L., Xu, Y.: SEGID:Identifying Interesting Segments in (Multiple) Sequence Alignments. Bioinformatics 19, 297–298 (2003)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chen, KY., Chao, KM. (2004). On the Range Maximum-Sum Segment Query Problem. In: Fleischer, R., Trippen, G. (eds) Algorithms and Computation. ISAAC 2004. Lecture Notes in Computer Science, vol 3341. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30551-4_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-30551-4_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24131-7

  • Online ISBN: 978-3-540-30551-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics