4. Model and Work with Graph Data Structures
Graphs are fundamental data structures that model relationships in various applications like social networks and routing systems. They can be represented through adjacency lists or matrices, each with its advantages and disadvantages. Key traversal algorithms such as Depth-First Search and Breadth-First Search facilitate the exploration of graph structures, while advanced algorithms provide solutions for shortest paths and tree constructions.
Sections
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What we have learnt
- Graphs consist of vertices and edges and are used to model complex relationships.
- There are various types of graphs including directed, undirected, weighted, and unweighted.
- Key graph algorithms include Depth-First Search, Breadth-First Search, Dijkstra’s, and Prim’s algorithm.
Key Concepts
- -- Graph
- A non-linear data structure consisting of nodes (vertices) and connections (edges) used to model relationships.
- -- Adjacency Matrix
- A 2D array representation of a graph where the presence of edges is indicated.
- -- Adjacency List
- A data structure that represents a graph by maintaining a list of neighbors for each vertex.
- -- DepthFirst Search (DFS)
- An algorithm used for traversing or searching tree or graph data structures, exploring as far as possible along a branch before backtracking.
- -- BreadthFirst Search (BFS)
- An algorithm for traversing or searching tree or graph data structures, exploring all neighbors at the present depth before moving on to nodes at the next depth level.
Additional Learning Materials
Supplementary resources to enhance your learning experience.