Data Mining for Complex Data Objects            

[Course Information] [Slides] [Reading Materials] [Assignments] [Data Mining Practice] 
Course Information
 
  Course Number: 30000580
  To: Undergraduate students of School of Artificial Intelligence, Nanjing University.
  Number of Students: 50
  Classroom: I-324, Main Teaching Building, Xianlin Campus
  Time: 10:00 -- 12:00, every Thursday
  Office Hour: 16:00 -- 17:00, every Thursday  (Rm 917)
Reference Book: [1] C. C. Aggarwal. Data Mining: The Textbook. Springer, 2015.
[2] J. Han, M. Kamber, J. Pei. Data Mining: Concepts and Techniques, 3rd edition. Elsevier Inc, 2012.
[3] D. Hand, H. Mannila, P. Smyth. Principles of Data Mining. MIT Press, MA:Cambridge, 2001.
Grading: Assignments (50%) + Data Mining Challenge (50%)
  TA: Mr. Jiang-Tian Xue and Mr. Wen-Jie Deng

                          

Slides      (The slides would appear on this web page just after the corresponding chapter is introduced.)
               Lecture 1:    Introduction
               Lecture 2:    Data and Its Preprocessing
               Lecture 3:    Data Mining Tasks and Techniques
               Lecture 4:    Mining the Text Data and Web
               Lecture 5:    Mining the Graph Data
               Lecture 6:    Mining the Social Network
               Lecture 7:    Mining the Software Data
 
Reading Materials
              Matrix Cookbook
 
 
Assignments 
              The Assignment 1 is released.  (Due on class at 12:00,Oct. 30). [Data and Requirements]
 
 
Data Mining Practice  
      The data mining practice is to apply data mining techniques to analyze academic data. Detailed information could be found here. (Reports due at 23:59, Dec. 24)