World and internet is full of textual information. We search for information using textual queries, we read websites, books, e-mails. All those are strings from the point of view of computer science. To make sense of all that information and make search efficient, search engines use many string algorithms. Moreover, the emerging field of personalized medicine uses many search algorithms to find disease-causing mutations in the human genome. In this online course you will learn key pattern matching concepts: tries, suffix trees, suffix arrays and even the Burrows-Wheeler transform.
제공자:
데이터 구조 및 알고리즘 특화 과정캘리포니아 샌디에고 대학교이 강좌에 대하여
최근 조회 23,189회
유연한 마감일
일정에 따라 마감일을 재설정합니다.
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 6개 강좌 중 4번째 강좌:
중급 단계
완료하는 데 약 19시간 필요
영어
자막: 아랍어, 프랑스어, 포르투갈어 (유럽), 이탈리아어, 베트남어, 독일어, 러시아어, 영어, 스페인어
귀하가 습득할 기술
- Suffix Tree
- Suffix Array
- Knuth–Morris–Pratt (KMP) Algorithm
- Algorithms On Strings
유연한 마감일
일정에 따라 마감일을 재설정합니다.
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 6개 강좌 중 4번째 강좌:
중급 단계
완료하는 데 약 19시간 필요
영어
자막: 아랍어, 프랑스어, 포르투갈어 (유럽), 이탈리아어, 베트남어, 독일어, 러시아어, 영어, 스페인어
제공자:
캘리포니아 샌디에고 대학교
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
강의 계획표 - 이 강좌에서 배울 내용
완료하는 데 5시간 필요
Suffix Trees
How would you search for a longest repeat in a string in LINEAR time? In 1973, Peter Weiner came up with a surprising solution that was based on suffix trees, the key data structure in pattern matching. Computer scientists were so impressed with his algorithm that they called it the Algorithm of the Year. In this lesson, we will explore some key ideas for pattern matching that will - through a series of trials and errors - bring us to suffix trees.
완료하는 데 5시간 필요
6개 동영상 (총 32분), 5 개의 읽기 자료, 2 개의 테스트
완료하는 데 5시간 필요
Burrows-Wheeler Transform and Suffix Arrays
Although EXACT pattern matching with suffix trees is fast, it is not clear how to use suffix trees for APPROXIMATE pattern matching. In 1994, Michael Burrows and David Wheeler invented an ingenious algorithm for text compression that is now known as Burrows-Wheeler Transform. They knew nothing about genomics, and they could not have imagined that 15 years later their algorithm will become the workhorse of biologists searching for genomic mutations. But what text compression has to do with pattern matching??? In this lesson you will learn that the fate of an algorithm is often hard to predict – its applications may appear in a field that has nothing to do with the original plan of its inventors.
완료하는 데 5시간 필요
5개 동영상 (총 30분), 4 개의 읽기 자료, 2 개의 테스트
완료하는 데 4시간 필요
Knuth–Morris–Pratt Algorithm
Congratulations, you have now learned the key pattern matching concepts: tries, suffix trees, suffix arrays and even the Burrows-Wheeler transform! However, some of the results Pavel mentioned remain mysterious: e.g., how can we perform exact pattern matching in O(|Text|) time rather than in O(|Text|*|Pattern|) time as in the naïve brute force algorithm? How can it be that matching a 1000-nucleotide pattern against the human genome is nearly as fast as matching a 3-nucleotide pattern??? Also, even though Pavel showed how to quickly construct the suffix array given the suffix tree, he has not revealed the magic behind the fast algorithms for the suffix tree construction!In this module, Miсhael will address some algorithmic challenges that Pavel tried to hide from you :) such as the Knuth-Morris-Pratt algorithm for exact pattern matching and more efficient algorithms for suffix tree and suffix array construction.
완료하는 데 4시간 필요
8개 동영상 (총 54분), 2 개의 읽기 자료, 1 개의 테스트
완료하는 데 6시간 필요
Constructing Suffix Arrays and Suffix Trees
In this module we continue studying algorithmic challenges of the string algorithms. You will learn an O(n log n) algorithm for suffix array construction and a linear time algorithm for construction of suffix tree from a suffix array. You will also implement these algorithms and the Knuth-Morris-Pratt algorithm in the last Programming Assignment in this course.
완료하는 데 6시간 필요
16개 동영상 (총 119분), 3 개의 읽기 자료, 2 개의 테스트
검토
- 5 stars66.16%
- 4 stars21.95%
- 3 stars7.88%
- 2 stars2.39%
- 1 star1.59%
문자열 알고리즘의 최상위 리뷰
AA 제공2017년 12월 29일
A good course giving insight into how important string algorithms are for not only to computer science community but also its use in other disciplines like bioinformatics etc.
PP 제공2016년 8월 15일
Really good quality information and examples (includes reasoning). It includes some of the latest developments in this area.
MT 제공2020년 8월 20일
Suffix Array and Suffix Tree was the hardest part so far from all the previous courses in this specialization
KP 제공2018년 6월 23일
Learned a lot in the class. It was really excellent. But many a times we need to hear twice to understand some of the concepts clearly.
데이터 구조 및 알고리즘 특화 과정 정보
Computer science legend Donald Knuth once said “I don’t understand things unless I try to program them.” We also believe that the best way to learn an algorithm is to program it. However, many excellent books and online courses on algorithms, that excel in introducing algorithmic ideas, have not yet succeeded in teaching you how to implement algorithms, the crucial computer science skill that you have to master at your next job interview. We tried to fill this gap by forming a diverse team of instructors that includes world-leading experts in theoretical and applied algorithms at UCSD (Daniel Kane, Alexander Kulikov, and Pavel Pevzner) and a former software engineer at Google (Neil Rhodes). This unique combination of skills makes this Specialization different from other excellent MOOCs on algorithms that are all developed by theoretical computer scientists. While these MOOCs focus on theory, our Specialization is a mix of algorithmic theory/practice/applications with software engineering. You will learn algorithms by implementing nearly 100 coding problems in a programming language of your choice. To the best of knowledge, no other online course in Algorithms comes close to offering you a wealth of programming challenges (and puzzles!) that you may face at your next job interview. We invested over 3000 hours into designing our challenges as an alternative to multiple choice questions that you usually find in MOOCs.
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