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Event Details

Jianwei Han, UIUC

4:00 p.m
March 4, 2009
Ford ITW Auditorium

Jiawei Han, Database and Information Systems Research Lab, Department of Computer Science, University of Illinois at Urbana-Champaign
"Mining, Indexing, and Searching Graphs in Large Data Sets"
Abstract: Recent research on pattern discovery has progressed from mining frequent itemsets and sequences to mining structured patterns including trees, lattices, and graphs. As a general data structure, graph can model complicated relations among data with wide applications in Web, social network analysis, and bioinformatics. However, mining and searching large graphs in graph databases is challenging due to the presence of an exponential number of frequent subgraphs. In this talk, we present our recent progress on developing efficient and scalable methods for mining and searching of graphs in large databases. We introduce gSpan and CloseGraph, two efficient methods for mining frequent graph patterns in graph databases. Then we introduce constraint-based graph mining methods. Further, we introduce a graph indexing method, gIndex, and a graph approximate searching method, grafil, both taking advantages of frequent graph mining to construct a compact but highly effective graph index and perform similarity search with such indexing structures. These methods not only facilitate mining and querying graph patterns in massive datasets but also claim broad applications in search and mining chemical compounds and biological networks.

Bio: Jiawei Han is a Professor in the Department of Computer Science at the University of Illinois since 2001. He was assistant professor at Northwestern Univ. in 1986-1987 after receiving his Ph.D. in Wisconsin in 1985. He has been working on research into data mining, data warehousing, stream data mining, spatiotemporal and multimedia data mining, biological data mining, social network analysis, text and Web mining, and software bug mining, with over 350 conference and journal publications. He has chaired or served in over 100 program committees of international conferences (as PC co-chair, vice-chair, tutorial chair, award chair, or PC member). He also served or is serving on the editorial boards for Data Mining and Knowledge Discovery, IEEE Transactions on Knowledge and Data Engineering, Journal of Computer Science and Technology, and Journal of Intelligent Information Systems. He is currently serving as founding Editor-in-Chief of ACM Transactions on Knowledge Discovery from Data (TKDD), and on the Board of Directors for the Executive Committee of ACM Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD). Jiawei has received three IBM Faculty Awards, the Outstanding Contribution Award at the 2002 International Conference on Data Mining, ACM Service Award (1999) and ACM SIGKDD Innovation Award (2004), and IEEE Computer Society Technical Achievement Award (2005). He is an ACM Fellow (2004). His book "Data Mining: Concepts and Techniques" (Morgan Kaufmann) has been used popularly as a textbook.

Jiawei Han's web page.

Hosted by Peter Scheuermann
Northwestern University Robert R. McCormick School of Engineering and Applied Science Electrical Engineering and Computer Science Department