Jiawei Han

Jiawei Han, Professor of Computer Science, University of Illinois at Urbana-Champaign. He has been researching into data mining, information network analysis, database systems, and data warehousing, with over 500 journal and conference publications. He has chaired or served on many program committees of international conferences, including PC co-chair for KDD, SDM, and ICDM conferences, and Americas Coordinator for VLDB conferences. He is currently the founding Editor-In-Chief of ACM Transactions on Knowledge Discovery from Data and as the Director of Information Network Academic Research Center supported by U.S. Army Research Lab. He is a Fellow of ACM and IEEE, and received 2004 ACM SIGKDD Innovations Award, 2005 IEEE Computer Society Technical Achievement Award, and 2009 IEEE Computer Society Wallace McDowell Award. His book “Data Mining: Concepts and Techniques” (2nd ed., Morgan Kaufmann, 2006) has been adopted as a textbook worldwide.

Publications

Applications of Pattern Discovery Using Sequential Data Mining
Applications of Pattern Discovery Using Sequential Data Mining
Manish Gupta, Jiawei Han. © 2013. 23 pages.
Sequential pattern mining methods have been found to be applicable in a large number of domains. Sequential data is omnipresent. Sequential pattern mining methods have been used...
Approaches for Pattern Discovery Using Sequential Data Mining
Approaches for Pattern Discovery Using Sequential Data Mining
Manish Gupta, Jiawei Han. © 2013. 17 pages.
In this chapter we first introduce sequence data. We then discuss different approaches for mining of patterns from sequence data, studied in literature. Apriori based methods and...
Foreword
Foreword
Jiawei Han. © 2012.
This Foreword is included in the book Social Network Mining, Analysis, and Research Trends: Techniques and Applications.
Applications of Pattern Discovery Using Sequential Data Mining
Applications of Pattern Discovery Using Sequential Data Mining
Manish Gupta, Jiawei Han. © 2012. 23 pages.
Sequential pattern mining methods have been found to be applicable in a large number of domains. Sequential data is omnipresent. Sequential pattern mining methods have been used...
Approaches for Pattern Discovery Using Sequential Data Mining
Approaches for Pattern Discovery Using Sequential Data Mining
Manish Gupta, Jiawei Han. © 2012. 18 pages.
In this chapter we first introduce sequence data. We then discuss different approaches for mining of patterns from sequence data, studied in literature. Apriori based methods and...
Ranking Gradients in Multi-Dimensional Spaces
Ranking Gradients in Multi-Dimensional Spaces
Ronnie Alves, Joel Ribeiro, Orlando Belo, Jiawei Han. © 2010. 19 pages.
Business organizations must pay attention to interesting changes in customer behavior in order to anticipate their needs and act accordingly with appropriated business actions....