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Faster range minimum queries

Authors: Tomasz Marek Kowalski; Szymon Grabowski;

Faster range minimum queries

Abstract

SummaryRange minimum query is an important building brick of many compressed data structures and string matching algorithms. Although this problem is essentially solved in theory, with sophisticated data structures allowing for constant time queries, practical performance and construction time also matter. Additionally, there are offline scenarios in which the number of queries, ie, q, is rather small and given beforehand, which encourages to use a simpler approach. In this work, we present a simple data structure, with very fast construction, which allows to handle queries in constant time on average. This algorithm, however, requires access to the input data during queries (which is not the case of sophisticated range minimum query solutions). We subsequently refine our technique, combining it with one of the existing succinct solutions with O(1) worst‐case time queries and no access to the input array. The resulting hybrid is still a memory frugal data structure, spending usually up to about 3n bits and providing competitive query times, especially for wide ranges. We also show how to make our baseline data structure more compact. Experimental results demonstrate that the proposed block‐based sparse table (BbST) variants are competitive to existing solutions, also in the offline scenario.

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Keywords

FOS: Computer and information sciences, Computer Science - Data Structures and Algorithms, Data Structures and Algorithms (cs.DS), 68W32, F.2.2

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Green