Keyword | CPC | PCC | Volume | Score | Length of keyword |
---|---|---|---|---|---|

tree data structure geeksforgeeks | 1.27 | 1 | 4187 | 48 | 33 |

tree | 0.22 | 0.1 | 1462 | 88 | 4 |

data | 0.63 | 0.1 | 3572 | 50 | 4 |

structure | 1.38 | 0.5 | 1894 | 61 | 9 |

geeksforgeeks | 0.25 | 0.4 | 4995 | 55 | 13 |

Keyword | CPC | PCC | Volume | Score |
---|---|---|---|---|

tree data structure geeksforgeeks | 0.33 | 0.1 | 4606 | 52 |

Binary Search Tree is a node-based binary tree data structure which has the following properties: The left subtree of a node contains only nodes with keys lesser than the node’s key. The right subtree of a node contains only nodes with keys greater than the node’s key. The left and right subtree each must also be a binary search tree.

Unlike Array and Linked List, which are linear data structures, tree is hierarchical (or non-linear) data structure. One reason to use trees might be because you want to store information that naturally forms a hierarchy. For example, the file system on a computer: Attention reader! Don’t stop learning now.

Store hierarchical data, like folder structure, organization structure, XML/HTML data. Binary Search Tree is a tree that allows fast search, insert, delete on a sorted data. It also allows finding closest item Heap is a tree data structure which is implemented using arrays and used to implement priority queues.

Basic Terminology In Tree Data Structure: Parent Node: The node which is a predecessor of a node is called the parent node of that node. { 2} is the parent node of { 6, 7}. Child Node: The node which is the immediate successor of a node is called the child node of that node. Examples: { 6, 7} are the child nodes of { 2}.