Find Strongly Connected Components in a Directed Graph: Difference between revisions

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=External=
* https://www.coursera.org/learn/algorithms-graphs-data-structures/lecture/rng2S/computing-strong-components-the-algorithm
* https://www.coursera.org/learn/algorithms-graphs-data-structures/lecture/QFOFt/computing-strong-components-the-analysis
=Internal=
=Internal=
* [[Graphs#Subjects|Graphs]]
* [[Graph#Directed_Graph_Connectivity|Directed Graph Connectivity]]
* [[Graph_Search#Depth-First_Search_.28DFS.29|Graph Search | Depth-First Search]]


=Overview=
=Overview=
Finding strongly connected components in a directed graph is a form of clustering heuristics: strongly connected components represent clusters where the objects represented by the vertices are clustered in some way.
Finding strongly connected components in a directed graph is a form of clustering heuristics: strongly connected components represent clusters where the objects represented by the vertices are clustered in some way.
[[Graph#Strongly_Connected_Component|Strongly connected components]] of a directed graph can be computed with two passes of [[Graph_Search#DFS_and_Directed_Connectivity_-_Compute_Strong_Components|depth-first search]]. This is the Kosaraju's Two-Pass Algorithms.
<font color=darkkhaki>TODO</font>

Revision as of 23:22, 1 October 2021

External

Internal

Overview

Finding strongly connected components in a directed graph is a form of clustering heuristics: strongly connected components represent clusters where the objects represented by the vertices are clustered in some way.

Strongly connected components of a directed graph can be computed with two passes of depth-first search. This is the Kosaraju's Two-Pass Algorithms.

TODO