- Open Bookshelf Cover Page
- Preface
- Getting Started
- Introduction to Recursion
- Divide and Conquer Algorithms
- Dynamic Programming
-
Binary Trees
- Intro to Trees
- Binary Trees
- Types of Binary Trees
- Divide & Conquer in Tree Problems
- Practice: Binary Tree Height
- Tree Traversal: DFS and BFS
- Practice: Preorder Traversal
- Practice: Inorder Traversal
- Practice: Postorder Traversal
- Practice: Level Order Traversal
- Binary Search Tree
- Practice: Find Node in a BST
- Graphs
- Backtracking
- Conclusion
- Share on
Introduction to Graphs
A graph is a collection of nodes that are connected in pairs. In data structures, these nodes are called vertices (singular: vertex), and the connections between them are known as edges. Graphs are incredibly useful for modeling relationships and connections in the real world, especially when dealing with interconnected entities.
Key Concepts
- Vertex: Also known as a node, a vertex represents a point in a graph where data can be stored. Vertices are essential components of a graph.
- Edge: An edge is a line that connects two vertices in a graph, establishing a relationship between them. Edges can be directed (one-way) or undirected (two-way).
Why Graphs Matter in the Real World
Graphs are invaluable because they can model so many different kinds of connections:
- Social Networks: Platforms like Facebook and LinkedIn use graphs to show who your friends are and how you're connected to others.
- Family Trees: Those charts showing your ancestors? They're graphs! They trace connections between family members across generations.
- Recommendations: Amazon's "Customers who bought this also bought..." feature uses graphs to show product relationships based on purchases.
- Navigation: Google Maps finds the best route to your destination by using a graph of roads and intersections.
In the next assignment, we'll dive into some of the most common and useful types of graphs.