Download METU Department of Computer Engineering CENG 514 Data

METU Department of Computer Engineering
CENG 514 Data Mining
Spring 2016-2017
Instructor
Pınar KARAGÖZ
Office: A404
Tel: 210 5518
e-mail: [email protected]
Lecture Hours
Monday 13.40 – 16.30
Room: A101
References
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Course Description
Data Mining: Concepts and Techniques, Jiawei Han and
Micheline Kamber, Morgan Kaufmann Publishers, ISBN
1558604898
Data Mining Introductory and Advanced Topics M.
Dunham, Prentice Hall
Data Mining Practical Machine Learning Tools and
Techniques Witten & Frank, Morgan Kaufmann
Introduction to Data Mining, PangNing Tan, Michael
Steinbach, Vipin Kumar, 2006, 0321321367
This course introduces data mining and data warehousing
concepts. Data warehousing, OLAP technology, data
preparation, association rule mining, classification and
prediction, clustering, mining complex types of data, web
mining, multi-relational data mining are the basic concepts
covered in this course.
Outline
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Introduction to data mining and data warehousing
Data warehousing and OLAP technology
Data preprocessing
Association rule mining
Classification and prediction
Clustering
A potpourri of advanced topics
Grading
Midterm
% 30
Assignments % 15
Paper Review % 5
Term Project % 25
Final Exam % 25
Weekly Schedule:
Week
Week 1
Feb. 20, 2017
Week 2
Feb. 27, 2017
Week 3
March 6, 2017
Week 4
March 13, 2017
Week 5
March 20, 2017
Week 6
March 27, 2017
Week 7
April 3, 2017
Week 8
April 10, 2017
Week 9
April 17, 2017
Week 10
April 24, 2017
Week 11
May 1, 2017
Week 12
May 8, 2017
Week 13
May 15, 2017
Week 14
May 22, 2017
May 29, 2016June 10, 2016
Topic
Notes
Introduction
Introduction, Association
Rule Mining
Association Rule Mining,
Classification Techniques
Classification and Clustering Assignment 1
Techniques
announcement
Clustering Techniques, Time
Series Analysis
Project Pres. - Phase I
Data Preprocessing, Data
Warehousing, OLAP
Assignment 1 due,
Paper selection for review
Assignment 2
announcement
Web Mining
Web Mining, Recommender
Systems
Assignment 2 due
Midterm
May 1 (No class)
Paper Review Presentations
Recommender Systems,
Mining on Social Networks,
Social Media
Mining on Social Networks,
Social Media
Final Exams
Paper review report due
Project final report and
demo
Notes:
• Late submission of assignments is not allowed.
• In case of providing legal excuse documents before the exam, students can
get make up for exams.