Research any topic before you write.

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

Matching (graph theory)

In the mathematical discipline of graph theory, a matching or independent edge set in an undirected graph is a set of edges without common vertices. In other words, a subset of the edges is a matching if each vertex appears in at most one edge of that matching.

Applications, Algorithms and computational complexity & Properties

Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.

Research this topic

Explore the main themes, entities and connections around Matching (graph theory). Start with the topic map, then use the sections below for research and deeper semantic analysis.

Explore this topic

Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.

Topics to explore

Browse the full topic structure. Each item opens a new analysis centered on that subject.

Overview

Definitions

Alternating and augmenting paths

Properties

Matching polynomials

Algorithms and computational complexity

Applications

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.

Map overview Semantic statistics

Matching (graph theory)

Nodes88
Edges87
Triples4
Avg. degree1.98
Density0.022727
Components1

How this topic connects Entity context

See the strongest relationship patterns around the current topic before diving into the raw triples.

Important terminology Word statistics

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

Important terminology

matching graph maximum problem number matchings bipartite edges edge perfect maximal algorithm graphs displaystyle vertices time vertex given also finding

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
bipartite planar graphsinstance ofand algorithms for special classes of graphs0.80text
as described in the main article.Maximum-weight matchingIn a weighted bipartite graphinstance ofand algorithms for special classes of graphs0.80text
the optimization problem is to find a maximum-weight matchinginstance ofand algorithms for special classes of graphs0.80text
as described in the main articleinstance ofand algorithms for special classes of graphs0.80text

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

    Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.

    Min side: 3
    For writers, content strategists, SEOs, marketers and creators — from quick topic research to advanced semantic analysis.