Graphs: Difference between revisions
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Graphs are backed by mathematical formalism. The [[Graph Concepts]] page provides a number of terms, concepts and some mathematical tools that are useful when dealing with graphs. [[Graph Representation in Memory]] describes ways to represent graph nodes and edges in such a way that they can be manipulated by algorithms. The most common arrangements - [[Graph_Representation_in_Memory#Adjacency_Lists|adjacency lists]] and [[Graph_Representation_in_Memory#Adjacency_Matrices|adjacency matrices]] - are discussed. | Graphs are backed by mathematical formalism. The [[Graph Concepts]] page provides a number of terms, concepts and some mathematical tools that are useful when dealing with graphs. [[Graph Representation in Memory]] describes ways to represent graph nodes and edges in such a way that they can be manipulated by algorithms. The most common arrangements - [[Graph_Representation_in_Memory#Adjacency_Lists|adjacency lists]] and [[Graph_Representation_in_Memory#Adjacency_Matrices|adjacency matrices]] - are discussed. | ||
The most obvious problem that arises when dealing with graphs is to walk them: search the graph or find paths through graphs, or more generically, explore a graph and infer knowledge about it. The classical algorithms for graph exploration are breadth-first search (BFS) and depth-first search (DFS). They are described and discussed in the [[Graph | The most obvious problem that arises when dealing with graphs is to walk them: search the graph or find paths through graphs, or more generically, explore a graph and infer knowledge about it. The classical algorithms for graph exploration are breadth-first search (BFS) and depth-first search (DFS). They are described and discussed in the [[Graph Search]] page. | ||
=Subjects= | =Subjects= | ||
* [[Graph Concepts]] | * [[Graph Concepts]] | ||
* [[Graph Representation in Memory]] | * [[Graph Representation in Memory]] | ||
Revision as of 19:10, 1 October 2021
Internal
Overview
Graphs are fundamental structures in computer science. They apply directly to a large number of problems that involve physical networks - such as the phone network or the internet, or logical networks about parallel relationships between objects in general - the order in which to execute interdependent tasks, or the analysis of social networks.
Graphs are backed by mathematical formalism. The Graph Concepts page provides a number of terms, concepts and some mathematical tools that are useful when dealing with graphs. Graph Representation in Memory describes ways to represent graph nodes and edges in such a way that they can be manipulated by algorithms. The most common arrangements - adjacency lists and adjacency matrices - are discussed.
The most obvious problem that arises when dealing with graphs is to walk them: search the graph or find paths through graphs, or more generically, explore a graph and infer knowledge about it. The classical algorithms for graph exploration are breadth-first search (BFS) and depth-first search (DFS). They are described and discussed in the Graph Search page.