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Space Efficient Data Structures for Nearest Larger Neighbor

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journal contribution
posted on 07.05.2015, 11:21 by V. Jayapaul, S. Jo, V. Raman, Rajeev Raman, S. R. Rao
Given a sequence of n elements from a totally ordered set, and a position in the sequence, the nearest larger neighbor (NLN) query returns the position of the element which is closest to the query position, and is larger than the element at the query position. The problem of finding all nearest larger neighbors has attracted interest due to its applications for parenthesis matching and in computational geometry [1, 2, 3]. We consider a data structure version of this problem, which is to preprocess a given sequence of elements to construct a data structure that can answer NLN queries efficiently. We consider time-space tradeoffs for the problem in both the encoding (where the input is not accessible after the data structure has been created) and indexing model, and consider cases when the input is in a one dimensional array, and also initiate the study of this problem on two-dimensional arrays.

History

Citation

Journal of Discrete Algorithms 2016, 36, pp. 63–75

Author affiliation

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

Version

AM (Accepted Manuscript)

Published in

Journal of Discrete Algorithms 2016

Publisher

Elsevier

issn

1570-8667

eissn

1570-8675

Copyright date

2015

Available date

25/02/2017

Publisher version

http://www.sciencedirect.com/science/article/pii/S1570866716000022

Language

en