NC State University
Department of Computer Science Colloquia 1999-2000
Date: Thursday, March 23, 2000
Time: 3:30 PM (talk)
Place: Withers 402A, NCSU Historical Campus (click for
courtesy parking request)
Speaker: Jiawei Han,
School of Computing Science, Simon Fraser University, Canada
Mining Frequent Patterns Without Candidate Generation
Abstract: As an active research theme in data mining, frequent pattern
mining covers a broad spectrum of data mining tasks, including mining various
kinds of association rules, correlations, causality, ratio rules, maximal
patterns, sequential patterns, episodes, partial periodicity, emerging
patterns, etc. Also, industry applications of frequent pattern mining have
gone far beyond simple "diapers and beers" legendary stories. In
this talk, I am going to first present a brief overview of technologies
for frequent pattern mining, with a focus on methods for frequent pattern
mining, sequential pattern mining, and constraint-based frequent pattern
mining. Then I am going to discuss an efficient mining method developed
by us recently, called mining frequent patterns without candidate generation.
This method eliminates the efforts of candidate generation and test, substantially
improves mining efficiency, and leads to high performance frequent pattern
mining with many possible extensions.
Short Bio: Jiawei Han
(Ph.D., Univ. of Wisconsin at Madison, 1985), Director of Intelligent Database
Systems Research Laboratory, and Endowed University Professor, School of
Computing Science, Simon Fraser University, Canada. He has conducted research
in the areas of data mining, data warehousing, spatial data mining, Web
mining, multimedia data mining, deductive and object-oriented databases,
and logic programming, with over 150 journal and conference publications.
He is a project leader of the Canada NCE/IRIS-3 project "Building, Querying,
Analyzing, and Mining Data Warehouses on the Internet" (1998-2002). He
has served or is currently serving in the program committees of over 50
international conferences and workshops, including SIGMOD'99, SIGKDD'99
(tutorial chairman), SIGMOD'2000 (demo chairman), EDBT'2000, and VLDB'2000.
He has also been serving as an editor for IEEE Transactions on Knowledge
and Data Engineering, Data Mining and Knowledge Discovery, and Journal
of Intelligent Information Systems. He is a co-author of the upcoming
textbook: "Data Mining: Concepts and Techniques" by Morgan Kaufmann.
Host: Donald
Bitzer, Computer Science, NCSU
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