Jiawei Han and Micheline Kamber
Data Mining: Concepts and Techniques, 2nd ed.
The Morgan Kaufmann Series in Data Management Systems, Jim Gray, Series
Editor
Morgan Kaufmann Publishers, March 2006. ISBN 1-55860-901-6
Slides
in PowerPoint form (will be updated without notice!)
Chapter 3. Data Warehouse and OLAP Technology: An Overview
Chapter 4. Data Cube Computation and Data Generalization
Chapter 5. Mining Frequent Patterns, Associations and Correlations
Chapter 6. Classification and Prediction
Chapter 8. Mining Stream, Time-Series and Sequence Data
Section 8.1. Mining Data Streams
Section 8.2. Mining Time-Series Data
Section 8.3. Mining Sequence Patterns in Transactional Databases
Section 8.4. Mining Sequence Patterns in Biological Databases
Chapter 9. Graph Mining, Social Network Analysis and Multi-Relational Data Mining
Section 9.2. Social Network Analysis
Section 9.3. Multirelational Data Mining
Chapter 10. Mining Object, Spatial, Multimedia, Text and Web Data
Section 10.1. Mining Object, Spatial and Multimedia Data
Section 10.1. Mining Text and Web Data
Chapter 11. Applications and Trends in Data Mining
Additional theme:
Visual Data Mining
Additional theme: Software Bug Mining
Additional theme: RFID Data Warehousing and High-Performance Data Mining
Additional theme: Intrusion Detection and Data Mining
Additional theme: Collaborative Filtering and Data Mining
Updated Slides for CS, UIUC Teaching in PowerPoint form (Note: This set of slides may not correspond to the textbook closely. In general, it takes new technical materials from recent research papers but shrinks some materials of the textbook. It has also rearranged the order of presentation for some technical materials.)
Chapter 3. Data Warehouse and OLAP Technology: An Overview
Chapter 4. Data Cube Computation and Data Generalization
Chapter 5. Mining Frequent Patterns, Associations and
Correlations
Chapter 6. Classification and Prediction