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For use as a data structure, the main alternative to the adjacency list is the adjacency matrix. Because each entry in the adjacency matrix requires only one bit, it can be represented in a very compact way, occupying only | V | 2 /8 bytes of contiguous space, where | V | is the number of vertices of the graph.
Adjacency list [2] Vertices are stored as records or objects, and every vertex stores a list of adjacent vertices. This data structure allows the storage of additional data on the vertices. Additional data can be stored if edges are also stored as objects, in which case each vertex stores its incident edges and each edge stores its incident ...
The adjacency matrix may be used as a data structure for the representation of graphs in computer programs for manipulating graphs. The main alternative data structure, also in use for this application, is the adjacency list. [11] [12]
Many graph-based data structures are used in computer science and related fields: Graph; Adjacency list; Adjacency matrix; Graph-structured stack; Scene graph; Decision tree. Binary decision diagram; Zero-suppressed decision diagram; And-inverter graph; Directed graph; Directed acyclic graph; Propositional directed acyclic graph; Multigraph ...
Neighbourhoods may be used to represent graphs in computer algorithms, via the adjacency list and adjacency matrix representations. Neighbourhoods are also used in the clustering coefficient of a graph, which is a measure of the average density of its neighbourhoods. In addition, many important classes of graphs may be defined by properties of ...
Pages in category "Graph data structures" The following 34 pages are in this category, out of 34 total. ... Abstract semantic graph; Adjacency list; Adjacency matrix;
The edges of a graph define a symmetric relation on the vertices, called the adjacency relation. Specifically, two vertices x and y are adjacent if {x, y} is an edge. A graph is fully determined by its adjacency matrix A, which is an n × n square matrix, with A ij specifying the number of connections from vertex i to vertex j.
For each vertex we store the list of adjacencies (out-edges) in order of the planarity of the graph (for example, clockwise with respect to the graph's embedding). We then initialize a counter = + and begin a Depth-First Traversal from . During this traversal, the adjacency list of each vertex is visited from left-to-right as needed.