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Rotating strings and particles in AdS: Holography at weak gaugecouplingand wi...
清华大学材料科学与工程研究院《材料科学论坛》:Next-generation Ultra-high-effi...
Mixed-state quantum anomaly and multipartite entanglement
Mass Gap in AdS Spacetime
报告题目:
Recent Research Progress in Frequent Pattern Mining
 报告人:
Jiawei Han
University of Illinois at Urbana-Champaign
报告时间:
2007-05-28 10:30
报告地点:
经管学院伟伦楼405
主办单位:
经管学院
  简介:

内容提要:

   Recent research progress in frequent pattern mining bring new promise in data mining applications in two aspects: (1) feature extraction for effective classification and (2) mining colossal patterns. My talk will cover the progress on these two themes based on our two recent research papers at ICDE'07. In the mean time, I am going to discuss a few promising research directions and predict their impacts on data mining.


演讲人简介

   Jiawei Han, Professor, Department of Computer Science, University of Illinois at Urbana-Champaign. He has been working on research into data mining, data warehousing, database systems, data mining from spatiotemporal data, multimedia data, stream and RFID data, social network data, and biological data, with over 300 journal and conference publications. He has chaired or served in over 100 program committees of international conferences and workshops, including PC co-chair of 2005 (IEEE) International Conference on Data Mining (ICDM), Americas Coordinator of 2006 International Conference on Very Large Data Bases (VLDB). He is also serving as the founding Editor-In-Chief of ACM Transactions on Knowledge Discovery from Data. He is an ACM Fellow and has received 2004 ACM SIGKDD Innovations Award and 2005 IEEE Computer Society Technical Achievement Award. His book "Data Mining: Concepts and Techniques" (2nd ed., Morgan Kaufmann, 2006) has been popularly used as a textbook worldwide.
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