Skip to main content

Inverse Range Selection Queries

  • Conference paper
  • First Online:
Book cover String Processing and Information Retrieval (SPIRE 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9954))

Included in the following conference series:

Abstract

On a given sequence \(X=\langle x_1x_2\ldots x_n \rangle \), the range selection queries denoted by Q(ijk) return the \(k^{th}\)-smallest element on \(\langle x_ix_{i+1}\ldots x_j \rangle \). The problem has received significant attention in recent years and many solutions aiming to achieve this task with a cost lower than dynamically sorting the elements on the queried range have been proposed. The reverse problem interestingly has not yet received that much attention, although there exists practical usage scenarios especially in the time–series analysis. This study investigates the inverse range selection query \( \bar{Q}(\upsilon ,k)\) that aims to detect all possible intervals on X such that the \(k^{th}\)-smallest element is less than or equal to \(\upsilon \). We present the basic solution first and then discuss how that basic solution can be implemented with different data structures previously proposed for regular range selection queries.

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 EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Notes

  1. 1.

    An integer \(x_i\) can be represented by \(\lfloor \log x_i \rfloor \) bits by omitting the leftmost 1 bit. We assume \(\log 0 = 0\) and process the integers 0 and 1 a bit differently on the wavelet tree. See [7, 8] for more details.

References

  1. Chan, T.M., Wilkinson, B.T.: Adaptive and approximate orthogonal range counting. In: Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 241–251 (2013)

    Google Scholar 

  2. Gagie, T., Puglisi, S.J., Turpin, A.: Range quantile queries: another virtue of wavelet trees. In: Karlgren, J., Tarhio, J., Hyyrö, H. (eds.) SPIRE 2009. LNCS, vol. 5721, pp. 1–6. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  3. Grossi, R., Gupta, A., Vitter, J.S.: High-order entropy-compressed text indexes. In: Proceedings of the 14th Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 841–850. SIAM (2003)

    Google Scholar 

  4. Hoare, C.A.R.: Algorithm 65: find. Commun. ACM 4(7), 321–322 (1961)

    Article  Google Scholar 

  5. Jørgensen, A.G., Larsen, K.G.: Range selection and median: tight cell probe lower bounds and adaptive data structures. In: Proceedings of the Twenty-Second Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 805–813 (2011)

    Google Scholar 

  6. Krizanc, D., Morin, P., Smid, M.: Range mode and range median queries on lists and trees. Nord. J. Comput. 12(1), 1–17 (2005)

    MathSciNet  MATH  Google Scholar 

  7. Külekci, M.O., Thankachan, S.V.: Range selection queries in data aware space and time. In: Data Compression Conference (DCC), pp. 73–82. IEEE (2015)

    Google Scholar 

  8. Külekci, M.O.: Enhanced variable-length codes: improved compression with efficient random access. In: Data Compression Conference (DCC), pp. 362–371. IEEE (2014)

    Google Scholar 

  9. Navarro, G.: Wavelet trees for all. In: Kärkkäinen, J., Stoye, J. (eds.) CPM 2012. LNCS, vol. 7354, pp. 2–26. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  10. Okanohara, D., Sadakane, K.: Practical entropy-compressed rank/select dictionary. In: Proceedings of the Meeting on Algorithm Engineering & Expermiments, pp. 60–70. Society for Industrial and Applied Mathematics, Philadelphia (2007). http://dl.acm.org/citation.cfm?id=2791188.2791194

  11. Petersen, H., Grabowski, S.: Range mode and range median queries in constant time and sub-quadratic space. Inform. Process. Lett. 109(4), 225–228 (2009)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgments

The author thanks to the anonymous reviewers of the paper for their valuable corrections and comments.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to M. Oğuzhan Külekci .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing AG

About this paper

Cite this paper

Külekci, M.O. (2016). Inverse Range Selection Queries. In: Inenaga, S., Sadakane, K., Sakai, T. (eds) String Processing and Information Retrieval. SPIRE 2016. Lecture Notes in Computer Science(), vol 9954. Springer, Cham. https://doi.org/10.1007/978-3-319-46049-9_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-46049-9_17

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46048-2

  • Online ISBN: 978-3-319-46049-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics