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Pattern Discovery in Data Mining
Course
en
English
16 h
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- Self-paced
- Free Access
- Fee-based Certificate
- 4 Sequences
- Introductive Level
Course details
Syllabus
- Week 1 - Course Orientation
The course orientation will get you familiar with the course, your instructor, your classmates, and our learning environment. - Week 1 - Module 1
Module 1 consists of two lessons. Lesson 1 covers the general concepts of pattern discovery. This includes the basic concepts of frequent patterns, closed patterns, max-patterns, and association rules. Lesson 2 covers three major approaches for mining frequent... - Week 2 - Module 2
Module 2 covers two lessons: Lessons 3 and 4. In Lesson 3, we discuss pattern evaluation and learn what kind of interesting measures should be used in pattern analysis. We show that the support-confidence framework is inadequate for pattern evaluation, and ev... - Week 3 - Module 3
Module 3 consists of two lessons: Lessons 5 and 6. In Lesson 5, we discuss mining sequential patterns. We will learn several popular and efficient sequential pattern mining methods, including an Apriori-based sequential pattern mining method, GSP; a vertic... - Week 4 - Week 4
Module 4 consists of two lessons: Lessons 7 and 8. In Lesson 7, we study mining quality phrases from text data as the second kind of pattern mining application. We will mainly introduce two newer methods for phrase mining: ToPMine and SegPhrase, and show fre...
Prerequisite
None.
Instructors
Jiawei Han
Abel Bliss Professor
Department of Computer Science
Editor
The University of Illinois at Urbana-Champaign was founded in 1867 (UIUC). The main campus of the University of Illinois is located in the twin cities of Champaign and Urbana, two hundred kilometres south of Chicago.
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