CS512: Data Mining Principles
Provide a comprehensive and in-depth introduction of the fundamental principles and techniques of data mining.
· Be able to understand the key concepts and underlying principles of data mining techniques, including frequent pattern mining, classification, clustering, deep learning, outlier detection, network mining.
· Be able to apply the key data mining techniques to realistic setting, evaluate and analyze the mining results.
Class meeting: online
· Instructor: Hanghang Tong (firstname.lastname@example.org)
o Qinghai Zhou (email@example.com)
o Zhe Xu (firstname.lastname@example.org)
Office Hours: [All CT time, all on Zooms. Note that each of us has a different zoom link & pwd. Please refer to announcement from compass2g/piazza]
· Hanghang Tong: 9-10am CT, Monday
· Qinghai Zhou: 9:00-9:40am Tuesday; 9:00-9:40pm Thursday
· Zhe Xu: 8:00-8:40pm Wednesday; 2:00-2:40pm Friday
· Piazza: http://piazza.com/illinois/spring2021/cs512
· Compass 2g
Schedule (Tentative, subject to slight adjustment)
· Logistics & Intro (week 1)
· Frequent Pattern Mining (weeks 2 & 3)
· Classification (weeks 4 & 5)
· Clustering (weeks 6 & 7)
· Deep Learning (week 8 & 9)
· Outlier & Anomaly Detection (week 10)
· Graph Connectivity Optimization (week 11)
· Network Science of Teams (week 12)
· NoX: Network-as-a-Context (week 13)
· Network Alignment (week 14)
· Fair Network Mining (week 15)
Coursework, Grading and Key Dates
· Two midterm exams: 40% in total (equal weights)
o First mid-term: 3/15/2021
o Second mid-term: 4/30/2021
· Two assignments: 30% in total (equal weights)
o First assignment: 2/1/2021 out; 3/5/2021 due
o Second assignment: 3/20/2021 out; 4/25/2021 due
· Class project: 30%
o Proposal (2%): due on 2/25/2021
o Mid-term report (8%): due on 3/30/2021
o Final report (20%): due on 5/5/2021
o Individual project or group project (3 members at most per group)
Required: Jiawei Han, Micheline Kamber and Jian Pei, Data Mining: Concepts and Techniques (3rd ed), Morgan Kaufmann, 2011
· Charu C. Aggarwal, Data Mining: The Textbook, Springer, 2015
· P.-N. Tan, M. Steinbach and V. Kumar, Introduction to Data Mining, Wiley, 2005 (2nd ed. 2016)
· Mohammed J. Zaki and Wagner Meira Jr., Data Mining and Analysis: Fundamental Concepts and Algorithms, Cambridge University Press, 2014
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