Space efficient data structures for nearest larger neighbor

被引：4

作者：

Jayapaul, Varunkumar ^{[1
]}

Jo, Seungbum ^{[2
]}

Raman, Rajeev ^{[3
]}

Raman, Venkatesh ^{[4
]}

Satti, Srinivasa Rao ^{[2
]}

机构：

[1] Chennai Math Inst, Madras, Tamil Nadu, India

[2] Seoul Natl Univ, Seoul 151, South Korea

[3] Univ Leicester, Leicester LE1 7RH, Leics, England

[4] Inst Math Sci, Madras, Tamil Nadu, India

来源：

JOURNAL OF DISCRETE ALGORITHMS | 2016年 / 36卷

关键词：

Nearest larger neighbor; Succinct data structures; Indexing model; Encoding model; Cartesian tree; Range minimum query;

D O I：

10.1016/j.jda.2016.01.001

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

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 the nearest larger neighbors of all the elements in a one-dimensional array has attracted interest due to its applications for parenthesis matching and in computational geometry [1-3]. 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 indexing and the encoding models when the input is in a one dimensional array, and also initiate the study of this problem on two-dimensional arrays. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：63 / 75

页数：13

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