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Applications, Advantages and Disadvantages of Unweighted Graph

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  • Last Updated : 23 Jun, 2022
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Unweighted graph is a type of graph with no edge weight. In an unweighted graph, the edges represent the connection between two nodes. If there is an edge between nodes u and v in an unweighted graph then u and v are adjacent to each other. 

Unweighted Graph

Applications of Unweighted Graph:

  • Unweighted graphs are used to represent data that are not related in terms of magnitude.
  • Unweighted graphs are used to represent computation flow. 

Real-Time Applications of Unweighted Graph:

  • Unweighted graphs can be used to solve puzzles.
  • It can be used to represent a circuit diagram.
  • It can be used in social media sites to find whether two users are connected or not.
  • It is used in Hamiltonian graphs which have many practical applications like genome mapping to combine many tiny fragments of genetic code.

Advantages of Unweighted Graph:

  • Unweighted graphs can be used to implement tree data structures.
  • Unweighted graphs are used in many algorithms like DFS and BFS.
  • Helps in optimal visualization of interrelated problems which are not related in terms of magnitude. 

Disadvantages:

  • The unweighted graphs do not have edge weight. Hence, cannot be used for shortest path evaluation or applications which require the distance between the nodes. 
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