What Are the Terminology of Graph in Data Structure?

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Angela Bailey

What Are the Terminology of Graph in Data Structure?

Graphs are widely used in computer science and data structures to represent various relationships and connections between objects. Understanding the terminology associated with graphs is essential for effectively working with them.

In this article, we will explore the key terminology used in graph theory and data structure.

Vertices and Edges

A graph consists of two fundamental components: vertices (also known as nodes) and edges. Vertices are the individual elements or objects within a graph, while edges represent the connections or relationships between vertices.

The vertices can be represented by circles or points, and the edges can be represented by lines connecting these points.

In HTML, we can represent vertices using a <ul> tag to create an unordered list, where each item represents a vertex using a <li> tag. For example:

<ul>
  <li>Vertex 1</li>
  <li>Vertex 2</li>
  <li>Vertex 3</li>
</ul>

Directed and Undirected Graphs

Graphs can be categorized as either directed or undirected based on the nature of their edges. In a directed graph, edges have a specific direction associated with them, indicating that they can only be traversed in a specific direction.

On the other hand, in an undirected graph, edges do not have any specific direction associated with them.

To visually represent directed and undirected graphs using HTML styling elements, we can use <b> tags to emphasize the terms. For example:

In a directed graph, the edges are represented by arrows indicating the direction of traversal.

In an undirected graph, the edges are represented by simple lines without any specific direction associated with them.

Weighted and Unweighted Graphs

Graphs can also be classified as either weighted or unweighted based on the presence or absence of weights associated with their edges. In a weighted graph, each edge is assigned a numerical value known as weight, which represents some kind of significance or cost associated with that edge.

In contrast, in an unweighted graph, all edges have equal significance or cost.

To denote weighted and unweighted graphs in our HTML content, we can use <ul> tags to create lists and <li> tags to represent each point. For example:

  • In a weighted graph, each edge is assigned a numerical weight.
  • In an unweighted graph, all edges have equal significance.

Adjacency and Degree of Vertices

The adjacency of vertices refers to whether two vertices in a graph are connected by an edge or not. The degree of a vertex is the number of edges connected to it.

It indicates how many connections or relationships a vertex has with other vertices in the graph.

To highlight these concepts within our HTML content, we can use headings (<h2>) for adjacency and degree of vertices:

Adjacency:

The adjacency between two vertices is determined by the presence of an edge connecting them.

Degree of Vertices:

The degree of a vertex is the number of edges connected to it.

Understanding these fundamental graph terminologies is crucial for working with graphs effectively in data structures and algorithms. By using HTML styling elements such as <b>, <u>, <ul>, <li>, and proper subheaders, we can visually engage readers and make the content more organized and appealing.

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