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Asymptotically Optimal Encodings of Range Data Structures for Selection and Top-k Queries

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posted on 01.12.2016, 09:47 by Roberto Grossi, John Iacono, Gonzalo Navarro, Rajeev Raman, S. Rao Satti
Given an array A[1, n] of elements with a total order, we consider the problem of building a data structure that solves two queries: (a) selection queries receive a range [i, j] and an integer k and return the position of the kth largest element in A[i, j]; (b) top-k queries receive [i, j] and k and return the positions of the k largest elements in A[i, j]. These problems can be solved in optimal time, O(1 + lg k/ lg lg n) and O(k), respectively, using linear-space data structures. We provide the first study of the encoding data structures for the above problems, where A cannot be accessed at query time. Several applications are interested in the relative order of the entries of A, and their positions, rather their actual values, and thus we do not need to keep A at query time. In those cases, encodings save storage space: we first show that any encoding answering such queries requires n lg k − O(n + k lg k) bits of space; then, we design encodings using O(n lg k) bits, that is, asymptotically optimal up to constant factors, while preserving optimal query time.

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Citation

ACM Transactions on Algorithms (TALG), 2017, 13(2)

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Computer Science

Version

AM (Accepted Manuscript)

Published in

ACM Transactions on Algorithms (TALG)

Publisher

Association for Computing Machinery (ACM)

issn

1549-6325

eissn

1549-6333

Acceptance date

26/10/2016

Copyright date

2017

Available date

10/03/2017

Publisher version

http://dl.acm.org/citation.cfm?doid=3040971.3012939

Language

en

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