文档介绍:Data Mining:
Concepts and Techniques
— Chapter 5 —
Jiawei Han
Department puter Science
University of Illinois at Urbana-Champaign
/~hanj
©2006 Jiawei Han and Micheline Kamber, All rights reserved
2011-1-19 School of Management, HUST 1
Chapter 5: Mining Frequent Patterns,
Association and Correlations
Basic concepts and a road map
Efficient and scalable frequent itemset mining
methods
Mining various kinds of association rules
From association mining to correlation
analysis
Constraint-based association mining
Summary
2011-1-19 School of Management, HUST 2
Chapter 5: Mining Frequent Patterns,
Association and Correlations
Basic concepts and a road map
Efficient and scalable frequent itemset mining
methods
Mining various kinds of association rules
From association mining to correlation
analysis
Constraint-based association mining
Summary
2011-1-19 School of Management, HUST 3
What Is Frequent Pattern Analysis?
Frequent pattern: a pattern (a set of items, subsequences, substructures,
etc.) that occurs frequently in a data set
First proposed by Agrawal, Imielinski, and Swami [AIS93] in the context
of frequent itemsets and association rule mining
Motivation: Finding inherent regularities in data
What products were often purchased together?— Beer and diapers?!
What are the subsequent purchases after buying a PC?
What kinds of DNA are sensitive to this new drug?
Can we automatically classify web documents?
Applications
Basket data analysis, cross-marketing, catalog design, sale campaign
analysis, Web log (click stream) analysis, and DNA sequence analysis.
2011-1-19 School of Management, HUST 4
Why Is Freq. Pattern Mining Important?
Discloses an intrinsic and important property of data sets
Forms the foundation for many essential data mining tasks
Association, correlation, and causality analysis
Sequential, structural (., sub-