Research any topic before you write.

Find related topics. | Discover entities. | See connections. | Build a topical map.

Fortune's algorithm: Algorithm description, Weighted sites and disks & Overview

Fortune's algorithm is a sweep line algorithm for generating a Voronoi diagram from a set of points in a plane using O(n log n) time and O(n) space. It was originally published by Steven Fortune in 1986 in his paper "A sweepline algorithm for Voronoi diagrams."

Language: English [EN]
Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.
100%
More settings
100% 100% 100% 100% 100%

Fortune's algorithm topic overview

The analysis highlights Algorithm description, Weighted sites and disks and Overview as prominent areas in the source structure around Fortune's algorithm.

Related topics
13
Source areas
3
Connected nodes
16
Extracted relationships
8
Concept neighborhoods
14
Bridge connections
16

What this topic covers Research coverage

Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.

Algorithm description · 7 topics
Overview · 3 topics
Weighted sites and disks · 3 topics

Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.

Explore all related topics Closing gaps

Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.

Overview

Algorithm description

Weighted sites and disks

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

How Fortune's algorithm connects Entity context

The extracted context around Fortune's algorithm shows recurring relationship patterns in the source. For example, Fortune's algorithm → Algorithm Visualization, August, Fortune's, GitHub, JavaScript, Steven Fortune's, Voronoi Another extracted example is Fortune's algorithm → sweep line algorithm for generating a Voronoi diagram from a set of points in a plane using O. Use these groups to spot repeated connection types before inspecting the individual relationships.

Fortune's algorithm

Top relations

related to External links · 7
Fortune's algorithm → Algorithm Visualization, August, Fortune's, GitHub, JavaScript, Steven Fortune's, Voronoi
is a · 1
Fortune's algorithm → sweep line algorithm for generating a Voronoi diagram from a set of points in a plane using O

Important terminology

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

Important terminology

line algorithm sweep voronoi beach diagram points sites parabolas plane time weighted may left point parabola using log diagrams disks

Fortune's algorithm relationships Subject–Predicate–Object triples

TTTA extracted 8 structured relationships around Fortune's algorithm. Examples in this analysis include Fortune's algorithm → is a → sweep line algorithm for generating a Voronoi diagram from a set of points in a plane using O and Fortune's algorithm → related to External links → Steven Fortune's. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
Fortune's algorithmis asweep line algorithm for generating a Voronoi diagram from a set of points in a plane using O0.90text
Fortune's algorithmrelated to External linksSteven Fortune's0.60section
Fortune's algorithmrelated to External linksVoronoi0.60section
Fortune's algorithmrelated to External linksFortune's0.60section
Fortune's algorithmrelated to External linksJavaScript0.60section
Fortune's algorithmrelated to External linksGitHub0.60section
Fortune's algorithmrelated to External linksAugust0.60section
Fortune's algorithmrelated to External linksAlgorithm Visualization0.60section

Related concept clusters Concept neighborhoods

The concept neighborhoods around Fortune's algorithm bring nearby vocabulary together. In this analysis, examples include Set, Steven and Data. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

  • Fortune's algorithm
    • Set
    • Steven
    • Data
    • Description
    • Fortune
    • Fortune's
    • Log
    • Maintains
    • Pseudocode
    • Structures
    • Using
    • Beach
  • fortune's algorithm
    • Voronoi
    • Line
    • Set
    • Steven
    • Time
    • Data
    • Description
    • Diagram
    • Fortune
    • Fortune's
    • Log
    • Maintains
  • sweep line algorithm
    • Sweep
    • Beach
    • Points
    • Voronoi
    • Line
    • Left
    • Parabola
    • Parabolas
    • Plane
    • Point
    • Time
    • Data
  • voronoi diagram
    • Voronoi
    • Time
    • Log
    • Weighted
    • Line
    • Sweep
    • Points
    • Set
    • Additively
    • Disks
    • Right
    • Straight
  • sweep line
    • Sweep
    • Beach
    • Points
    • Voronoi
    • Left
    • Parabola
    • Parabolas
    • Plane
    • Point
    • Input
    • Progresses
    • Right
  • weighted voronoi diagram
    • Sites
    • Additively
    • Diagrams
    • Disks
    • Voronoi
    • Time
    • Fortune
    • Log
    • Weighted
    • Line
    • Sweep
    • May
  • algorithm description
    • Pseudocode
    • Voronoi
    • Line
    • Fortune
    • Maintains
    • Steven
    • Time
    • Additively
    • Data
    • Description
    • Diagram
    • Diagrams
  • weighted sites and disks
    • Additively
    • Sites
    • Weighted
    • Diagrams
    • Disks
    • Fortune
    • Voronoi
    • May
    • Maintains
    • Pseudocode
    • Set
    • Steven

Connections between topic areas Semantic bridges

For Fortune's algorithm, one of the stronger structural bridges in this analysis connects Fortune's algorithm with Algorithm description. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.

Min side: 3
Fortune's algorithm — Algorithm description · splits 9 ⟂ 8
Fortune's algorithm — Overview · splits 13 ⟂ 4
Fortune's algorithm — Weighted sites and disks · splits 13 ⟂ 4

Map overview Semantic statistics

Fortune's algorithm

Nodes17
Edges16
Triples8
Avg. degree1.88
Density0.117647
Components1

Source & methodology

TTTA analyzes the structure around Fortune's algorithm to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Algorithm description, Weighted sites and disks & Overview, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — Fortune's algorithm · EN edition · Analysis: TopicsToTalkAbout

For writers, content strategists, SEOs, marketers and creators — from quick topic research to advanced semantic analysis.