ENEE752: Computational Intelligence and Knowledge Engineering, Fall 2009

Instructor: Joseph JaJa     Contact Information: joseph@umiacs.umd.edu  301-405-1925                             

Office Hours (3433 A.V. Williams Bldg): M,W 4-5:15 or by appointment

Course Objectives: The course will cover core topics in machine learning and their applications to data mining and knowledge discovery. Topics include: statistical learning models; decision trees; rule-based and nearest neighbor classifiers; neural networks; Bayesian networks; support vector machines; clustering; and ensemble methods.

Textbook: Introduction to Data Mining, Tan, Steinback and Kumar, Pearson, Addison-Wesley, 2006.

Course Syllabus

Exams: Midterms (October 7 and November 18) Paper (due December 15)

Preliminary References for Web Data Mining:

• Web Mining and Web Usage Analysis: http://webmining.spd.louisville.edu/webkdd08/
• Mining the Web, Soumen Chakrabarti, Morgan-Kaufman, 2002: http://www.cse.iitb.ac.in/~soumen/mining-the-web/
• Web Data Mining, Bing Liu, Springer, 2006: http://www.cs.uic.edu/~liub/WebMiningBook.html
• Web Mining Research: A Survey, R. Kosala and H. Blockeel, 2000.

Assignments:

Homework #1: Due Wednesday, September 16 - Problems 13, 14, 15, 18, 24 from Chapter 2. Solutions

Homework#2: Due Wednesday, September 23 - Problems 3, 5, 6 from Chapter 4. Solutions

Homework#3: Due Wednesday, September 30 - Problems 7, 9, 10 from Chapter 4 Solutions

Homework#4: Due Wednesday, October 7 - Problems 4, 5 from Chapter 5 Solutions

Homework#7: Due Wednesday, November 4 - Problems 7, 8, 10, 12 from Chapter 5 Solutions