2021년 2월 17일 (수) 07:54에 Pythagoras0님의 편집

2021-02-17T07:54:37Z

Pythagoras0: /* 메타데이터 */ 새 문단

2020-12-26T12:10:51Z

메타데이터: 새 문단

Pythagoras0: /* 노트 */ 새 문단

2020-12-21T15:08:10Z

노트: 새 문단

새 문서

== 노트 ==

===위키데이터===
* ID : [https://www.wikidata.org/wiki/Q189057 Q189057]
===말뭉치===
# Merge sort is a sorting technique based on divide and conquer technique.<ref name="ref_d6266c02">[https://www.tutorialspoint.com/data_structures_algorithms/merge_sort_algorithm.htm Merge Sort Algorithm]</ref>
# We know that merge sort first divides the whole array iteratively into equal halves unless the atomic values are achieved.<ref name="ref_d6266c02" />
# Merge sort keeps on dividing the list into equal halves until it can no more be divided.<ref name="ref_d6266c02" />
# We shall now see the pseudocodes for merge sort functions.<ref name="ref_d6266c02" />
# The first algorithm we will study is the merge sort.<ref name="ref_8d55604a">[https://runestone.academy/runestone/books/published/pythonds/SortSearch/TheMergeSort.html 6.11. The Merge Sort — Problem Solving with Algorithms and Data Structures]</ref>
# Merge sort is a recursive algorithm that continually splits a list in half.<ref name="ref_8d55604a" />
# If the list has more than one item, we split the list and recursively invoke a merge sort on both halves.<ref name="ref_8d55604a" />
# Figure 10 shows our familiar example list as it is being split by mergeSort .<ref name="ref_8d55604a" />
# As shown in the image below, the merge sort algorithm recursively divides the array into halves until we reach the base case of array with 1 element.<ref name="ref_8d75d944">[https://www.programiz.com/dsa/merge-sort Merge Sort Algorithm]</ref>
# Merge sort is one of the most efficient sorting algorithms.<ref name="ref_9a68c695">[https://www.interviewbit.com/tutorial/merge-sort-algorithm/ Merge Sort Algorithm With Example Program]</ref>
# The top-down merge sort approach is the methodology which uses recursion mechanism.<ref name="ref_9a68c695" />
# The Bottom-Up merge sort approach uses iterative methodology.<ref name="ref_9a68c695" />
# In computer science, merge sort (also commonly spelled mergesort) is an efficient, general-purpose, comparison-based sorting algorithm.<ref name="ref_921551b8">[https://en.wikipedia.org/wiki/Merge_sort Merge sort]</ref>
# A natural merge sort is similar to a bottom-up merge sort except that any naturally occurring runs (sorted sequences) in the input are exploited.<ref name="ref_921551b8" />
# In the bottom-up merge sort, the starting point assumes each run is one item long.<ref name="ref_921551b8" />
# In the typical case, the natural merge sort may not need as many passes because there are fewer runs to merge.<ref name="ref_921551b8" />
# Call mergeSort for first half: Call mergeSort(arr, l, m) 3.<ref name="ref_f61d2d10">[https://www.geeksforgeeks.org/merge-sort/ GeeksforGeeks]</ref>
# Call mergeSort for second half: Call mergeSort(arr, m+1, r) 4.<ref name="ref_f61d2d10" />
# The following diagram from wikipedia shows the complete merge sort process for an example array {38, 27, 43, 3, 9, 82, 10}.<ref name="ref_f61d2d10" />
# WriteLine( "Given Array" ); printArray(arr); MergeSort ob = new MergeSort(); ob.sort(arr, 0, arr.<ref name="ref_f61d2d10" />
# extra space is of no concern, then merge sort is an excellent choice: It is simple to implement, and it is the only stable O(n·lg(n)) sorting algorithm.<ref name="ref_99c12c9e">[https://www.toptal.com/developers/sorting-algorithms/merge-sort Merge Sort - Sorting Algorithm Animations]</ref>
# The idea behind this paper is to modify the conventional Merge Sort Algorithm and to present a new method with reduced execution time.<ref name="ref_6cd6848a">[https://www.sciencedirect.com/science/article/pii/S1877050916315381 Enhanced Merge Sort- A New Approach to the Merging Process ☆]</ref>
# The newly proposed algorithm is faster than the conventional Merge Sort algorithm having a time complexity of O(n log 2 n).<ref name="ref_6cd6848a" />
# In this article, we will see the logic behind Merge Sort, implement it in JavaScript, and visualize it in action.<ref name="ref_4d2eeba4">[https://stackabuse.com/merge-sort-in-javascript/ Merge Sort in JavaScript]</ref>
# Merge sort uses the concept of divide-and-conquer to sort the given list of elements.<ref name="ref_4d2eeba4" />
# As we now have the code to merge two sorted arrays (conquer part of divide-and-conquer), let us write the final code for our Merge Sort algorithm.<ref name="ref_4d2eeba4" />
# Unlike Quick Sort, Merge Sort is not an in-place sorting algorithm, meaning it takes extra space other than the input array.<ref name="ref_4d2eeba4" />
# In Merge Sort, the given unsorted array with n elements, is divided into n subarrays, each having one element, because a single element is always sorted in itself.<ref name="ref_5bf426c6">[https://www.studytonight.com/data-structures/merge-sort Merge Sort Algorithm]</ref>
# Mergesort is used when we want a guaranteed running time of O ( n log ⁡ n ) O(n \log n) O(nlogn), regardless of the state of the input.<ref name="ref_a9469817">[https://brilliant.org/wiki/merge/ Brilliant Math & Science Wiki]</ref>
# Merge sort is a “divide and conquer” algorithm wherein we first divide the problem into subproblems.<ref name="ref_7a31be0c">[https://www.baeldung.com/java-merge-sort Merge Sort in Java]</ref>
# For the implementation, we'll write a mergeSort function which takes in the input array and its length as the parameters.<ref name="ref_7a31be0c" />
# Chapter 11, Parallel patterns: merge sort, introduces merge sort, and dynamic input data identification and organization.<ref name="ref_6669dae6">[https://www.sciencedirect.com/topics/computer-science/merge-sort Merge-Sort - an overview]</ref>
# In Mergesort, we take the mid index which is (beg index + end index)/2.<ref name="ref_3aa76d2a">[https://www.mygreatlearning.com/blog/merge-sort/ Merge Sort Algorithms and Examples]</ref>
# But in merge sort in every iteration, we create two new temporary arrays.<ref name="ref_3aa76d2a" />
# This brings us to the end of this article where we learned about merge sort and its implementation in various languages.<ref name="ref_3aa76d2a" />
# def mergesort(n): """Recursively merge sort a list.<ref name="ref_08cca053">[https://sites.google.com/site/cbnualgteam/MergeSort 전북대학교 알고리즘 5 조 분할 정복]</ref>
# The first called mergeSort , which is the function we’ll call, and another one called _mergeArrays , which takes care of merging the arrays.<ref name="ref_9f3b2d08">[https://flaviocopes.com/merge-sort-javascript/ JavaScript Algorithms: Merge Sort]</ref>
# Merge sort is the algorithm which follows divide and conquer approach.<ref name="ref_07a21aef">[https://www.javatpoint.com/merge-sort Merge Sort]</ref>
# Conquer means sort the two sub-arrays recursively using the merge sort.<ref name="ref_07a21aef" />
# The main idea behind merge sort is that, the short list takes less time to be sorted.<ref name="ref_07a21aef" />
# Sort the array by using merge sort.<ref name="ref_07a21aef" />
# In this post, we're going to learn a similar algorithm to quick sort -- merge sort.<ref name="ref_fb549734">[https://www.honeybadger.io/blog/ruby-merge-sort/ Exploring Merge Sort with Ruby]</ref>
# Merge sort was invented by John von Neumann in 1945.<ref name="ref_fb549734" />
# At a high level, the merge sort algorithm splits the array into two sub-arrays again and again (utilizing recursion) until only one element remains.<ref name="ref_fb549734" />
# Unlike bubble sort and other similar algorithms, merge sort is difficult to understand without visualization.<ref name="ref_fb549734" />
# Sort the two subsequences recursively by re-applying merge sort.<ref name="ref_f03767b5">[https://www.bogotobogo.com/Algorithms/mergesort.php Merge Sort]</ref>
# On the other hand, merge sort is a stable sort, parallelizes better, and is more efficient at handling slow-to-access sequential media.<ref name="ref_f03767b5" />
# Merge sort illustrated through a Transylvanian-saxon (German) folk dance.<ref name="ref_08ecd9dd">[https://xlinux.nist.gov/dads/HTML/mergesort.html merge sort]</ref>
# Merge sort is a divide and conquer algorithm.<ref name="ref_1d40920a">[https://www.techiedelight.com/merge-sort/ C++, Java and Python Implementation]</ref>
# Like all divide and conquer algorithms, merge sort divides a large array into two smaller subarrays and then recursively sort the subarrays.<ref name="ref_1d40920a" />
# sort array 'arr' using auxiliary array 'aux' mergeSort ( arr , aux , 0 , arr .<ref name="ref_1d40920a" />
# So here's mergesort, a divide and conquer sorting algorithm.<ref name="ref_81de6756">[https://www.usna.edu/Users/cs/wcbrown/courses/S18SI335/lec/l10/lec.html SI335: All about Merge Sort]</ref>
# In class we made a start on analyzing mergesort.<ref name="ref_81de6756" />
# This version of Merge Sort only needs n locations to sort.<ref name="ref_0e9ec767">[https://rosettacode.org/wiki/Sorting_algorithms/Merge_sort Sorting algorithms/Merge sort]</ref>
# * half and perform a merge sort on each half .<ref name="ref_0e9ec767" />
# Alternatively, we can use bottom-up mergesort.<ref name="ref_0e9ec767" />
# but for the fact that merge sort needs the array to be of one element, it will keep splicing that half till it fulfills the condition of having one element array.<ref name="ref_d7b630af">[https://dev.to/mcfrank16/understanding-merge-sort-in-javascript-4cne Merge Sort JavaScript Understanding Merge Sort in Javascript.]</ref>
# The task is develop a merge sort algorithm that "splits" the input array recursively into k arrays.<ref name="ref_5f64d052">[https://stackoverflow.com/questions/61705366/merge-sort-in-k-parts merge sort in k parts]</ref>
# I initially coded two methods to merge sort with two parts, namely merge sort and merge.<ref name="ref_5f64d052" />
# Now we get can start digging into some of the more efficient big boy algorithms, like merge sort.<ref name="ref_15b3f6e5">[https://www.digitalocean.com/community/tutorials/js-understanding-merge-sort Understanding Merge Sort Through JavaScript]</ref>
# Similar to binary search, merge sort is a divide and conquer algorithm.<ref name="ref_15b3f6e5" />
# Merge sort is built off the idea of comparing whole arrays instead of individual items.<ref name="ref_15b3f6e5" />
# “Merge sort” is popular algorithm for sorting an array from smallest to largest.<ref name="ref_c84ae506">[https://blog.codeanalogies.com/2020/02/02/merge-sort-explained-by-trying-to-become-a-tennis-champion/ Merge Sort Explained By Trying To Become A Tennis Champion]</ref>
# So, this guide will give an incredibly simple explanation of how merge sort actually works.<ref name="ref_c84ae506" />
# So, using merge sort, we need to rank this group from lowest skill to highest skill.<ref name="ref_c84ae506" />
# Mergesort guarantees to sort an array of N items in time proportional to N log N, no matter what the input.<ref name="ref_63daf859">[https://algs4.cs.princeton.edu/22mergesort/ Mergesort]</ref>
# Merge.java is a recursive mergesort implementation based on this abstract in-place merge.<ref name="ref_63daf859" />
# We can cut the running time of mergesort substantially with some carefully considered modifications to the implementation.<ref name="ref_63daf859" />
# Mergesort is an asymptotically optimal compare-based sorting algorithm.<ref name="ref_63daf859" />
# For example, if an array is to be sorted using mergesort, then the array is divided around its middle element into two sub-arrays.<ref name="ref_f111c25b">[https://www.softwaretestinghelp.com/merge-sort-java/ Program To Implement MergeSort]</ref>
# Let’s see the pseudo-code for the Mergesort technique.<ref name="ref_f111c25b" />
# In the above pseudo-code, we have two routines i.e. Mergesort and merge.<ref name="ref_f111c25b" />
# The routine Mergesort splits the input array into an individual array that is easy enough to sort.<ref name="ref_f111c25b" />
# Perhaps the most useful application of the merge method is a sorting algorithm known as merge sort.<ref name="ref_6f1e3935">[http://www2.lawrence.edu/fast/GREGGJ/CMSC150/042Sorting/Sorting.html Merge Sort]</ref>
# What prevents that problem here is the fact that the two arrays created by mergeSort are smaller than the original.<ref name="ref_6f1e3935" />
# This method, Arrays.sort() is even faster than merge sort and also does not require a temporary array to do its work.<ref name="ref_6f1e3935" />
# A merge sort uses a technique called divide and conquer.<ref name="ref_b8ba996b">[https://www.bbc.co.uk/bitesize/guides/zjdkw6f/revision/5 GCSE Computer Science Revision]</ref>
# function mergeSort ( array ){ let midpoint = array .<ref name="ref_b78dbdc0">[https://learn.co/lessons/merge-sort-big-o Merge Sort Big O]</ref>
# Compare the big o of merge sort with that of selection sort.<ref name="ref_b78dbdc0" />
# So when is one thousand selection sort takes over a hundred times longer than merge sort.<ref name="ref_b78dbdc0" />
# We calculate the big O of mergeSort by remembering that the big O of merging is equal to the length of our two subarrays combined.<ref name="ref_b78dbdc0" />
# Note that each of these piles is individually sorted already -- that is always true with merge sort.<ref name="ref_6cbc95a5">[https://github.com/raywenderlich/swift-algorithm-club/tree/master/Merge%20Sort swift-algorithm-club/Merge Sort at master · raywenderlich/swift-algorithm-club · GitHub]</ref>
# Frequently used algorithms to sort arrays of data in NoSQL databases is merge sort, where as NoSQL we understand any database without typical SQL programming interpreter.<ref name="ref_01fc7dbb">[https://www.mdpi.com/2073-8994/9/9/176 Parallelization of Modified Merge Sort Algorithm]</ref>
# The method is compared to other sorting methods like quick sort, heap sort, and merge sort to show potential efficiency.<ref name="ref_01fc7dbb" />
# The idea we describe in this article is based on modified merge sort, which in parallel form is designed for multicore architectures.<ref name="ref_5733bbc2">[https://www.hindawi.com/journals/complexity/2018/8679579/ Fully Flexible Parallel Merge Sort for Multicore Architectures]</ref>
# Merge sort was improved by new ideas of sublinear methods and various approaches to parallelization.<ref name="ref_5733bbc2" />
# Quick sort, heap sort, and merge sort were also mixed and derived to present new methods of sorting.<ref name="ref_5733bbc2" />
# The research on improvements for merge sort gave new, faster processing of input string but also improved management of the data during iterations in the algorithm.<ref name="ref_5733bbc2" />
# Here, we present a parallel version of the well-known mergesort algorithm.<ref name="ref_b37b0c2c">[https://www.mcs.anl.gov/~itf/dbpp/text/node127.html 11.4 Mergesort]</ref>
# We next describe the parallel mergesort algorithm proper.<ref name="ref_b37b0c2c" />
# First, each task sorts its local sequence using sequential mergesort.<ref name="ref_b37b0c2c" />
# Parallel mergesort uses the hypercube communication template at multiple levels.<ref name="ref_b37b0c2c" />
===소스===
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-== 메타데이터 ==
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 * ID :  [https://www.wikidata.org/wiki/Q189057 Q189057]

← 이전 판		2020년 12월 26일 (토) 12:10 판
98번째 줄:		98번째 줄:
	===소스===		===소스===
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		+	== 메타데이터 ==
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		+	===위키데이터===
		+	* ID : [https://www.wikidata.org/wiki/Q189057 Q189057]

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2021년 2월 17일 (수) 07:54에 Pythagoras0님의 편집

Pythagoras0: /* 메타데이터 */ 새 문단

Pythagoras0: /* 노트 */ 새 문단