Representing modelling knowledge in an intelligent decision support system
Decision Support Systems
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
PARSIMONY: An infrastructure for parallel multidimensional analysis and data mining
Journal of Parallel and Distributed Computing - Special issue on high-performance data mining
Characterization and parallelization of decision-tree induction
Journal of Parallel and Distributed Computing - Special issue on high-performance data mining
Parallel sequence mining on shared-memory machines
Journal of Parallel and Distributed Computing - Special issue on high-performance data mining
Approaches to parallel graph-based knowledge discovery
Journal of Parallel and Distributed Computing - Special issue on high-performance data mining
Corporate Information Factory
Exploration Warehousing
Management Decision Systems: Computer-Based Support for Decision Making
Management Decision Systems: Computer-Based Support for Decision Making
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
IPDPS '00 Proceedings of the 14th International Symposium on Parallel and Distributed Processing
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In recent years, new decision support system (DSS) based on the technologies of data warehouse, data mining and on-line analytical processing appeared. As the accumulated amount of data becomes enormous too much, the data quantitative problem, the data qualitative problem and the data presentation problem occur in data mining in large-scale databases and data warehouses. An effective way to enhance the power and flexibility of data mining in data warehouses and large databases is to integrate data mining with OLAP in DSS. Parallel and distributed processing are also two important components of successful large-scale data mining applications. In this paper, a high performance data mining scheme is proposed. The overall architecture and the mechanism of the system are described.