Applications of Min-Heap Data Structure
- Heap sort: Min heap is used as a key component in heap sort algorithm which is an efficient sorting algorithm with a time complexity of O(nlogn).
- Priority Queue: A priority queue can be implemented using a min heap data structure where the element with the minimum value is always at the root.
- Dijkstra’s algorithm: In Dijkstra’s algorithm, a min heap is used to store the vertices of the graph with the minimum distance from the starting vertex. The vertex with the minimum distance is always at the root of the heap.
- Huffman coding: In Huffman coding, a min heap is used to implement a priority queue to build an optimal prefix code for a given set of characters.
- Merge K sorted arrays: Given K sorted arrays, we can merge them into a single sorted array efficiently using a min heap data structure.
Introduction to Min-Heap – Data Structure and Algorithm Tutorials
A Min-Heap is defined as a type of Heap Data Structure in which each node is smaller than or equal to its children.
The heap data structure is a type of binary tree that is commonly used in computer science for various purposes, including sorting, searching, and organizing data.
Purpose and Use Cases of Min-Heap:
- Implementing Priority Queue: One of the primary uses of the heap data structure is for implementing priority queues.
- Dijkstra’s Algorithm: Dijkstra’s algorithm is a shortest path algorithm that finds the shortest path between two nodes in a graph. A min heap can be used to keep track of the unvisited nodes with the smallest distance from the source node.
- Sorting: A min heap can be used as a sorting algorithm to efficiently sort a collection of elements in ascending order.
- Median finding: A min heap can be used to efficiently find the median of a stream of numbers. We can use one min heap to store the larger half of the numbers and one max heap to store the smaller half. The median will be the root of the min heap.
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