2. 2016/2/4Course Introduction1 COMP 4332, RMBI 4330 Advanced Data Mining (Spring 2012) Qiang Yang Hong Kong University of Science and Technology qyang@cs.ust.hk http://www.cs.ust.hk

3. Topics Review of Basics Practical Data Mining Imbalanced Data Streaming and Time Series Data Big Data Social Recommendation Social Media and Social Networks Hands on: 2 Major Projects Student Presentations 2016/2/4Course Introduction2

4. Outcome and Objective Student will know the current state of the art in Data Mining Student will be able to implement a practical data mining project Student will be able to present their ideas well Prepared for PG study, Internship, etc. 2016/2/4Course Introduction3

5. Projects: based on KDDCUPs Project 1: KDDCUPs on credit rating and customer retention (KDDCUP 2009) Project 2: Yahoo! Music Recommendation (KDDCUP 2011) Project 3 (Optional): KDDCUP 2012 2016/2/4Course Introduction4

6. 2016/2/4Course Introduction5 5 KDDCUP Examples — KDDCUP from past years — 2007: — Predict if a user is going to rate a movie? — Predict how many users are going to rate a movie? — 2006: — Predict if a patient has cancer from medical images — 2005: — Given a web query ( “ Apple ” ), predict the categories (IT, Food) — 1998: — Given a person, predict if this person is going to donate money — In general, we wish to — Input: Data — Output: — Build model — Apply model to future data

7. 2016/2/4Course Introduction6 Important Sites  Instructor Web Site  http://www.cse.ust.hk/~qyang/4332 http://www.cse.ust.hk/~qyang/4332  TA: Yin Zhu and Kaixiang Mo  Assignment Hand-in: online  comp4332@cse.ust.hk  Course Discussion Site:  Check out the web cite…

8. 2016/2/4Course Introduction7 Prerequisites  Statistics and Probability would help,  But will be reviewed in class  Machine Learning/Pattern Recognition would help,  We will review some most important algorithms  One programming language  We will teach new languages in the tutorial

9. 2016/2/4Course Introduction8 Grading  Assignments 10%  Course Projects and Presentations: 50%  Final Exam 40%

10. 2016/2/4Course Introduction9 More info Textbooks: Listed on Course Website Buy them online if you wish