KDD-2001 Tutorial
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| Abstract | Presenters | ||
| Knowledge discovery and data mining (KDD) deal with the problem of extracting interesting associations, classifiers, clusters, and other patterns from data. KDD is playing an increasingly important role in business, scientific, and engineering applications because of the growing availability of data in electronic format. The advent of laptops, palmtops, cell phones, and wearable computers is also making ubiquitous access to large quantity of data possible. Advanced analysis of data for extracting useful knowledge is the next natural step in the world of ubiquitous computing. This will integrate KDD into our increasingly mobile but connected lifestyle and offer technology to monitor time-critical information collected at different locations from anywhere. This will introduce a new generation of applications in many domains such as finance, health, service, manufacturing industries, and sensor networks for defense applications. This tutorial will review the state-of-the-art technology for ubiquitous data mining (UDM) in mobile and distributed environments. Accessing and analyzing data from a ubiquitous computing device offer many challenges. For example, the benefits of ubiquitous presence usually do not come for free. UDM introduces additional cost due to communication, computation, security, and other factors. So one of the objectives of UDM is to mine data while minimizing the cost of ubiquitous presence. Human-computer interaction is another challenging aspect of UDM. Visualizing patterns like, classifiers, clusters, associations and others, in portable devices is usually difficult. The small display areas offer serious challenges to interactive data mining environments. Data management in a mobile environment is also a challenging issue. This tutorial will present (1) an overview of UDM applications for distributed environments, (2) different data analysis algorithms for UDM, (3) human-computer interaction issues, (4) system development and (5) data management issues. |
Hillol Kargupta
is an Assistant Professor in the Department of Computer
Science and Electrical Engineering, University of Maryland Baltimore
County. He received his Ph.D. in Computer Science from University of
Illinois at Urbana-Champaign in 1996. His research interests include
mobile and distributed data mining, computation in gene expression, and
genetic algorithms.
Dr. Kargupta won a National Science Foundation (NSF) CARRER award in 2001 for his research on ubiquitous and distributed data mining. His research is also funded by several other grants from NSF and NASA. He also received support from the TRW Research Foundation, American Cancer Society, US Department of Energy, and Caterpillar. He won the 1997 Los Alamos Award for Outstanding Technical Achievement. His dissertation earned him the 1996 Society for Industrial and Applied Mathematics (SIAM) annual best student paper prize. He has published more than fifty peer-reviewed articles in journals, conferences, and books. He is the distributed data mining consultant for DaimlerChrysler. He is the primary editor of a book entitled "Advances in Distributed and Parallel Knowledge Discovery", AAAI/MIT Press. His other recent activities include hosting the ACM SIGKDD-2000 workshop on Distributed and Parallel Knowledge Discovery (DPKD), KDD-98 workshop on distributed data mining, a special issue on DPKD in Knowledge and Information Systems Journal. He is the co-chair of the IJCAI-2001 Workshop on Wrappers for Performance Enhancement in Knowledge Discovery in Databases. He is in the program/organizing committee for the 2001 & 2002 SIAM Data Mining Conference and the 2001 ACM SIGKDD Conference among several others. He is also the co-chair of a workshop on ubiquitous data mining in PKDD-2001. More information about him can be found at http://www.cs.umbc.edu/~hillol. Anupam Joshi is an Assistant Professor of Computer Science and Electrical Engineering at UMBC. Earlier, he was an Assistant Professor in the CECS department at the University of Missouri, Columbia, and a Visiting Assistant Professor at Purdue. He obtained a B. Tech degree in Electrical Engineering from IIT Delhi in 1989, and a Masters and Ph.D. in Computer Science from Purdue University in 1991 and 1993 respectively. His research interests are in the broad area of networked computing and intelligent systems, with a particular emphasis on mobile computing. He has worked on the problem of creating intelligent agent based middleware to support mobile access to networked computing and multimedia information resources. Presently, he is investigating data management and distributed computation issues for ad-hoc networks, as well as m-commerce. He is also interested in Web Mining & Personalization, Content-based retrieval of video data from networked repositories, and networked HPCC. He has published over 50 technical papers, and has obtained research support from IBM, AetherSystems, AT&T, Intel, DoD, and NSF (including a CAREER award). He is an associate editor for IEEE Trans. Fuzzy Systems. He has presented tutorials in conferences, served as guest editor for special issues for IEEE Personal Comm., CACM, etc., and has served on several program committees, including those of MobiCom 98 and 99. He referees for several journals and conferences, and has served on NSF IIS and DUE panels. He is a member of ACM(4352688), IEEE, and UPE. He may be reached at joshi@cs.umbc.edu , http://www.cs.umbc.edu/~joshi/ |
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