Graph and tree are the non-linear data structure which is used to solve various complex problems. A graph is a group of vertices and edges where an edge connects a pair of vertices whereas a tree is considered as a minimally connected graph which must be connected and free from loops.
Conclusion. So, the difference between tree search and graph search is not that tree search works on trees while graph search works on graphs! Both can work on trees or graphs (but, given that graphs are a generalization of trees, we can simply say that both work on graphs, either trees or not) and both produce a tree!
Differences between tree and graph data structure. A Graph is also a non-linear data structure. In tree data structure, there is a unique node known as a parent node. It represents the topmost node in the tree data structure. In graph data structure, there is no unique node.
A Tree is just a restricted form of a Graph.
Trees have direction (parent / child relationships) and don't contain cycles. They fit with in the category of Directed Acyclic Graphs (or a DAG). So Trees are DAGs with the restriction that a child can only have one parent.
One thing that is important to point out, Trees aren't a recursive data structure. They can not be implemented as a recursive data structure because of the above restrictions. But any DAG implementation, which are generally not recursive, can also be used. My preferred Tree implementation is a centralized map representation and is non recursive.
Graphs are generally searched breadth first or depth first. The same applies to Tree.
Instead of explaining I prefer to show it in pictures.
A tree in real time
A graph in real life use
Yes a map can be visualised as a graph data structure.
Seeing them like this makes life easier. Trees are used at places where we know that each node has only one parent. But graphs can have multiple predecessors(term parent is generally not used for graphs).
In real world, you can represent almost anything using graphs. I used a map, for example. If you consider each city as a node, it can be reached from multiple points. The points which lead to this node are called predecessors and the points which this node will lead to are called successors.
electrical circuit diagram, the plan of a house, computer network or a river system are few more examples of graphs. Many real world examples can be considered as graphs.
Technical diagram could be like this
Tree :
Graph :
Make sure to refer to below links. Those will answer almost all your questions on trees and graphs.
References :
http://www.introprogramming.info/english-intro-csharp-book/read-online/chapter-17-trees-and-graphs/#_Toc362296541
http://www.community-of-knowledge.de/beitrag/data-trees-as-a-means-of-presenting-complex-data-analysis/
Wikipedia
The other answers are useful, but they're missing the properties of each:
Undirected graph, image source: Wikipedia
Directed graph, image source: Wikipedia
Could be directed or undirected (which would apply to all edges in the graph)
As per Wikipedia:
For example, if the vertices represent people at a party, and there is an edge between two people if they shake hands, then this graph is undirected because any person A can shake hands with a person B only if B also shakes hands with A. In contrast, if any edge from a person A to a person B corresponds to A admiring B, then this graph is directed, because admiration is not necessarily reciprocated.
Image source: Wikipedia
There is some overlap in the above properties. Specifically, the last two properties are implied by the rest of the properties. But all of them are worth noting nonetheless.
Tree is special form of graph i.e. minimally connected graph and having only one path between any two vertices.
In graph there can be more than one path i.e. graph can have uni-directional or bi-directional paths (edges) between nodes
Also you can see more details: http://freefeast.info/difference-between/difference-between-trees-and-graphs-trees-vs-graphs/
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