From 19df0066f3e94e2287631077801551e5e6d3e30d Mon Sep 17 00:00:00 2001 From: Hanney Date: Sat, 14 Jan 2017 13:45:56 +0900 Subject: [PATCH] translated "Graph" --- translations/README-ko.md | 30 +++++++++++++++--------------- 1 file changed, 15 insertions(+), 15 deletions(-) diff --git a/translations/README-ko.md b/translations/README-ko.md index 0c7b326..a5aa9e7 100644 --- a/translations/README-ko.md +++ b/translations/README-ko.md @@ -922,20 +922,20 @@ Anki format의 내 flashcard 데이터베이스: https://ankiweb.net/shared/info If you need more detail on this subject, see "Sorting" section in [Additional Detail on Some Subjects](#additional-detail-on-some-subjects) -## Graphs +## 그래프 -Graphs can be used to represent many problems in computer science, so this section is long, like trees and sorting were. +그래프는 컴퓨터 과학의 여러 문제들을 표현하는 데 사용할 수 있다. 때문에 이 섹션은 트리나 정렬 섹션처럼 길다. -- Notes from Yegge: - - There are three basic ways to represent a graph in memory: - - objects and pointers - - matrix - - adjacency list - - Familiarize yourself with each representation and its pros & cons - - BFS and DFS - know their computational complexity, their tradeoffs, and how to implement them in real code - - When asked a question, look for a graph-based solution first, then move on if none. +- Yegge의 노트: + - 메모리에 그래프를 표시하는 세 가지 기본 방법이 있다: + - 오브젝트와 포인터 + - 행렬 + - 인접 리스트 + - 각각의 표현과 장단점을 숙지하라. + - 넓이우선탐색(BFS)와 깊이우선탐색(DFS) - 계산상의 복잡성, 장단점, 실제 코드로 구현하는 방법을 알아야 한다. + - 질문을 받을 시 먼저 그래프 기반 솔루션을 찾고, 없을 경우에 다른 솔루션으로 넘어가라. -- [ ] Skiena Lectures - great intro: +- [ ] Skiena의 강좌 - 훌륭한 인트로: - [ ] [CSE373 2012 - Lecture 11 - Graph Data Structures (video)](https://www.youtube.com/watch?v=OiXxhDrFruw&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=11) - [ ] [CSE373 2012 - Lecture 12 - Breadth-First Search (video)](https://www.youtube.com/watch?v=g5vF8jscteo&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=12) - [ ] [CSE373 2012 - Lecture 13 - Graph Algorithms (video)](https://www.youtube.com/watch?v=S23W6eTcqdY&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=13) @@ -943,7 +943,7 @@ Graphs can be used to represent many problems in computer science, so this secti - [ ] [CSE373 2012 - Lecture 15 - Graph Algorithms (con't 2) (video)](https://www.youtube.com/watch?v=ia1L30l7OIg&index=15&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - [ ] [CSE373 2012 - Lecture 16 - Graph Algorithms (con't 3) (video)](https://www.youtube.com/watch?v=jgDOQq6iWy8&index=16&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) -- [ ] Graphs (review and more): +- [ ] 그래프 (검토, 그 외 여러가지): - [ ] [6.006 Single-Source Shortest Paths Problem (video)](https://www.youtube.com/watch?v=Aa2sqUhIn-E&index=15&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - [ ] [6.006 Dijkstra (video)](https://www.youtube.com/watch?v=2E7MmKv0Y24&index=16&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) @@ -961,14 +961,14 @@ Graphs can be used to represent many problems in computer science, so this secti - Full Coursera Course: - [ ] [Algorithms on Graphs (video)](https://www.coursera.org/learn/algorithms-on-graphs/home/welcome) -- Yegge: If you get a chance, try to study up on fancier algorithms: +- Yegge: 기회가 된다면, 더 멋진 알고리즘을 연구해 보라: - [ ] Dijkstra's algorithm - see above - 6.006 - [ ] A* - [ ] [A Search Algorithm](https://en.wikipedia.org/wiki/A*_search_algorithm) - [ ] [A* Pathfinding Tutorial (video)](https://www.youtube.com/watch?v=KNXfSOx4eEE) - [ ] [A* Pathfinding (E01: algorithm explanation) (video)](https://www.youtube.com/watch?v=-L-WgKMFuhE) -- I'll implement: +- 내가 구현할 것: - [ ] DFS with adjacency list (recursive) - [ ] DFS with adjacency list (iterative with stack) - [ ] DFS with adjacency matrix (recursive) @@ -984,7 +984,7 @@ Graphs can be used to represent many problems in computer science, so this secti - [ ] list strongly connected components - [ ] check for bipartite graph -You'll get more graph practice in Skiena's book (see Books section below) and the interview books +Skiena의 책(아래의 책 섹션 참조)과 인터뷰 책에서 더 많은 그래프 실습을 할 수 있다. ## Even More Knowledge