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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