To be Held in Conjunction with the
7th IEEE International Conference on Data Mining
(ICDM 2007)
With the rapid development of software and hardware, the data size and dimensionality being collected are increasing dramatically. High performance (parallel, distributed, grid-based) algorithms are crucial to any successful data mining solution. Instead of focusing on faster clock speeds and more powerful single-core CPUs, the trend clearly goes towards multi-core systems. Therefore, supercomputers, large-scale distributed computing infrastructures, and grid-based computing environments provide new opportunities for high performance data mining. Research on the corresponding algorithms must hence be kept on the forefront of this fast evolving field in order to keep pushing the performance envelope of data mining applications to meet the requirements. In addition, any novel large-scale data mining process or applications are welcome.
The goal of this workshop is to bring researchers and practitioners together in a setting where they can discuss the design, implementation, and deployment of large-scale, parallel, distributed, or grid-based data mining systems, which can manipulate data obtained from very large enterprise or scientific databases, regardless of whether the data are located centrally or are globally distributed.
- Novel large-scale data mining applications and algorithms
- Scalable parallel and distributed data mining algorithms
- Grid-based data mining systems (middleware and system design)
- Streaming data mining algorithms and systems
- Data mining with heterogeneous data sources (e.g. the Web, sequence data)
- Incremental and interactive data mining
- Frameworks for parallel or distributed data mining
- Agent-based approaches for high performance data mining
- Parallel data mining work flow management
- Special-purpose architectures for high performance data mining
- Memory management techniques for mining very large data sets
- Performance analysis for large data mining systems
All submissions should be submitted electronically, by the submission deadline of July 4, 2007, 23:59PST. Please submit it to the conference paper submission system All submissions should be made in PDF or PostScript format. Submissions should be a maximum of 6 pages and should use IEEE two column format.
All papers accepted for workshops will be included in the Workshop Proceedings published by the IEEE Computer Society Press and will be available at the workshops.
Submitted papers will be reviewed by members of the workshop program committee.
Alok Choudhary, Northwestern University, USA
Ying Liu, Graduate University of Chinese Academy of Sciences, Research Center on Data Technology and Knowledge Economy of Chinese Academy of Sciences
Jayaprakash Pisharath, Intel Corporation, USA
(for inquiries please contact Dr. Liu at yingliu@gucas.ac.cn.
Program Committee
Wei-keng Liao, Northwestern University, USA
Zhiling Lan, Illinois Institute of Technology, USA
Xingquan Zhu, Florida Atlantic University, USA
Yingjie Tian, Research Center on Data Technology and Knowledge Economy of Chinese Academy of Sciences
Steve Chiu, Idaho State University, USA
Joseph Zambreno, Iowa State University, USA
Jun Xu, Microsoft Research Asia
Ying Zhao, Tsinghua University, China
Jing He, Research Center on Data Technology and Knowledge Economy of Chinese Academy of Sciences
Cheng Wang, Agilent Technologies