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Transcript 
Copyright © 2004 Pearson Education, Inc.
Chapter 27
Data Mining Concepts
Copyright © 2004 Pearson Education, Inc.
Overview of Data Mining
Technology
Elmasri and Navathe, Fundamentals of Database Systems, Fourth Edition
Copyright © 2004 Pearson Education, Inc.
Slide 27-3
Association Rules
 Market-Basket Model, Support, and Confidence
 Apriori Algorithm
 Sampling Algorithm
 Frequent-Pattern Tree Algorithm
 Partition Algorithm
 Other Types of Association Rules
 Additional Considerations for Association Rules
Elmasri and Navathe, Fundamentals of Database Systems, Fourth Edition
Copyright © 2004 Pearson Education, Inc.
Slide 27-4
Classification
Elmasri and Navathe, Fundamentals of Database Systems, Fourth Edition
Copyright © 2004 Pearson Education, Inc.
Slide 27-5
Clustering
Elmasri and Navathe, Fundamentals of Database Systems, Fourth Edition
Copyright © 2004 Pearson Education, Inc.
Slide 27-6
Approaches to Other Data
Mining Problems
Discovery of Sequential Patterns
Discovery of Patterns in Time Series
Regression
Neural Networks
Genetic Algorithm
Elmasri and Navathe, Fundamentals of Database Systems, Fourth Edition
Copyright © 2004 Pearson Education, Inc.
Slide 27-7
Applications of Data Mining
Elmasri and Navathe, Fundamentals of Database Systems, Fourth Edition
Copyright © 2004 Pearson Education, Inc.
Slide 27-8
Commercial Data Mining
Tools
Elmasri and Navathe, Fundamentals of Database Systems, Fourth Edition
Copyright © 2004 Pearson Education, Inc.
Slide 27-9
Summary
Elmasri and Navathe, Fundamentals of Database Systems, Fourth Edition
Copyright © 2004 Pearson Education, Inc.
Slide 27-10
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