COMP3420 lecture slides for 2009 (subject to dynamic changes without notice)


Lecture No Date Viewing Printing Notes Lecturer Chapters (textbook)
Lecture 1 (1hr) Feb 24 ppt, pdf pdf Introduction to DW & DM Weifa Liang Chap 1
Lecture 2 (2hrs) Feb 25 ppt pdf Relation between DW & DM Weifa Liang Chap 1 & 3
Lecture 3 (1hr) March 3 lec. 03 ppt, lec.03 pdf, lec.3 pdf Overview of data preprocessing/Descriptive data summarization Weifa Liang Chapter 2
Lecture 4 (2hrs) March 4 lec. 04 ppt, lec.04 pdf, lec.04 pdf Data Cleaning/Data Integration/Data Transformation Weifa Liang Chapter 2
Lecture 5 (1hr) March 10 lec. 05 ppt, lec.05 pdf, lec.05 pdf Data reduction Weifa Liang Chapter 2
Lecture 6 (2hrs) March 11 lec.06 pdf, lec.06 pdf Data Linkage and Geocode matching Peter Christen Not covered in text book!
Lecture 7 (1hr) March 17 lec. 05b ppt, lec.05b pdf, lec.05b pdf Data discretization and concept hierarchy generation and summary Weifa Liang Chapter 2
Lecture 8 (2hrs) March 18 lec. 07 ppt, lec.07 pdf lec.07 pdf Data Warehousing (A multi-dimensional data model) Weifa Liang Chapter 3
  March 24   no lecture  
Lecture 9 (2hrs) March 25 lec. 08 ppt, lec.08 pdf,, OLAPoperation pdf, lec.08 pdf Data Warehousing (Data warehouse architecture
Data warehouse implementation)
Weifa Liang Chapter 3
Lecture 10 (1hr) March 31 lec. 09 ppt, lec.09 pdf, lec.09 pdf Data Cube Computation (I) Weifa Liang Chapter 4
Lecture 11 (2hrs) April 1 lec. 09b ppt, lec.09 pdf, lec.09 pdf Data Cube Computation (II) Weifa Liang Chapter 4
Mid Semester Break (Friday 10 April - Sunday 26 April)
Lecture 12 (1hr) April 28 DM-12.pdf DM-12-print.pdf Introduction to association mining Denny Chapter 4
Lectures 13 and 14 (2hrs) April 29 DM-13.pdf
DM-14.pdf
DM-13-print.pdf
DM-14-print.pdf
Advanced association mining
Introduction to cluster analysis
Denny Chapters 4 and 7
Lecture 15 (1hr) May 5 DM-15.pdf DM-15-print.pdf Advanced cluster analysis Denny Chapter 7
Lectures 16 and 17 (2hrs) May 6 DM-16.pdf
DM-17.pdf
DM-16-print.pdf
DM-17-print.pdf
Classification and prediction:
Introduction and decision trees
Bayesian classification and evaluating classifier accuracy
Denny Chapter 6
Lecture 18 (1hr) May 12 DM-18.pdf DM-18-print.pdf Classification and prediction:
Rule-based classification and artificial neural networks
Denny Chapter 6
Lecture 19 (1hr) May 13 DM-19.pdf DM-19-print.pdf Classification and prediction:
Support vector machines,
other classification methods, and prediction
Denny Chapter 6
Lecture 20 (1hr) May 19 DM-20.pdf DM-20-print.pdf Mining data streams and time series Denny Chapter 8
(Sections 1 and 2)
Lectures 21 and 22 (2hrs) May 21 DM-21.pdf
DM-22.pdf
DM-21-print.pdf
DM-22-print.pdf
Text data mining and Web data mining Denny Chapter 10
(Sections 4 and 5)
Lecture 23 (1hr) May 26 DM-23.pdf DM-23-print.pdf Privacy-preserving data mining and data sharing Peter Christen Not covered in text book!
Lecture 24 (1hr) June 2 DM-Exam.pdf DM-Exam-print.pdf Course review and exam preparation Weifa Liang and
Peter Christen