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Range searching

In computer science, the range searching problem consists of processing a set S of objects, in order to determine which objects from S intersect with a query object, called the range. For example, if S is a set of points corresponding to the coordinates of several cities, find the subset of cities within a given range of latitudes and longitudes.

Applications & Science

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Explore the main themes, entities and connections around Range searching. Start with the topic map, then use the sections below for research and deeper semantic analysis.

Explore this topic

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Topics to explore

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Overview

Variations

Data structures

Applications

Advanced semantic analysis

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Map overview Semantic statistics

Range searching

Nodes44
Edges43
Triples49
Avg. degree1.95
Density0.045455
Components1

How this topic connects Entity context

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Range searching

Top relations

related to Further reading · 15
Range searching → ACM Computing Surveys, Berg, Berlin, Computational Geometry, Geometric, ISBN, Jiří, Kreveld, Marc, Mark, Otfried, Overmars, S2CID, Schwarzkopf, Springer-Verlag
related to Variations · 13
Range searching → Algorithms, Both, Dynamic, If, In, Object, Offline, Query, Range, Some, Sometimes, The, There
related to Orthogonal range searching · 11
Range searching → Bentley, Bernard Chazelle, Big, Dan Willard, In, Jon Bentley, Joseph JaJa, RAM, Thus, While, With
related to Dynamic range searching · 6
Range searching → Both, For, In, Kurt Mehlhorn, Stefan Näher, While
has application · 3
Range searching → Colored, For, In

Important terminology Word statistics

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

range query searching problem points displaystyle time set orthogonal dynamic log data space objects also case counting dimensions consists intersect

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
geographical information systemsinstance ofApplications of the problem arise in areas0.80text
Range searchinghas applicationIn0.60section
Range searchinghas applicationColored0.60section
Range searchinghas applicationFor0.60section
Range searchingrelated to Dynamic range searchingWhile0.60section
Range searchingrelated to Dynamic range searchingIn0.60section
Range searchingrelated to Dynamic range searchingFor0.60section
Range searchingrelated to Dynamic range searchingKurt Mehlhorn0.60section
Range searchingrelated to Dynamic range searchingStefan Näher0.60section
Range searchingrelated to Dynamic range searchingBoth0.60section
Range searchingrelated to Further readingBerg0.60section
Range searchingrelated to Further readingMark0.60section

Related concept clusters Concept neighborhoods

These clusters group vocabulary that occurs around closely connected concepts in the source material.

    Connections between topic areas Semantic bridges

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    Min side: 3
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