Chapter 7 Flashcards

1
Q

is a non-linear data structure consisting of vertices and edges.

A

Graph

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2
Q

the fundamental units of the graph

A

Vertices

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3
Q

drawn or used to connect two nodes of the graph.

A

Edges

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4
Q

A graph is known as a __ if there are no edges in the graph.

A

null graph

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5
Q

Graph having only a single vertex, it is also the smallest graph possible

A

Trivial Graph

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6
Q

The graph in which from one node we can visit any other node in the graph is known as a

A

Connected Graph

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7
Q

The graph in which at least one node is not reachable from a node is known as a

A

Disconnected Graph

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8
Q

The graph in which the degree of every vertex is equal to K is called

A

Regular Graph

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9
Q

The graph in which from each node there is an edge to each other node.

A

Complete Graph

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10
Q

The graph in which the graph is a cycle in itself, the degree of each vertex is 2.

A

Cycle Graph

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11
Q

A graph containing at least one cycle is known

A

Cyclic Graph

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12
Q

A Directed Graph that does not contain any cycle.

A

Directed Acyclic Graph

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13
Q

A graph in which vertex can be divided into two sets such that vertex in each set does not contain any edge between them.

A

Bipartite Graph

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14
Q

A graph in which the edges are already specified with suitable weight

A

Weighted Graph

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15
Q

the restricted types of graphs, just with some more rules.

A

Trees

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16
Q

Two ways to store a graph:

A

Adjacency Matrix
Adjacency List

17
Q

can be used to represent the interactions between players on a team, such as passes, shots, and tackles

A

Graph data structures

18
Q

Can be used to represent the topology of computer networks, such as the connections between routers and switches.

A

Graphs

19
Q

are used to represent the connections between different places in a transportation network, such as roads and airports

A

Graphs

20
Q

real-life applications of graph

A

1.Neural Networks
2.Compilers
3.Robot planning

21
Q

used to search a graph data structure for a node that meets a set of criteria.

A

TheBreadth First Search (BFS)algorithm

22
Q

similar toDepth First Traversal of a tree.The only catch here is, that, unlike trees, graphs may contain cycles (a node may be visited twice).

A

Depth First Traversal (or DFS)for a graph

23
Q

an algorithm for traversing or searching tree or graph data structures.

A

Depth-first search

24
Q

A graph has a cycle if and only if we see a back edge during DFS

A

Detecting cycle in a graph

25
Q

mainly used for scheduling jobs from the given dependencies among jobs.

A

Topological Sorting