An architecture for distributed enterprise data mining

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Abstract

The requirements for data mining systems for large organisations and enterprises range from logical and physical distribution of large data and heterogeneous computational resources to the general need for high performance at a level that is sufficient for interactive work. This work categorises the requirements and describes the Kensington software architecture that addresses these demands. The system is capable of transparently supporting parallel computation at two levels, and we describe a configuration for trans-atlantic distributed parallel data mining that was demonstrated at the recent Supercomputing conference.

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Chattratichat, J., Darlington, J., Guo, Y., Hedvall, S., Köhler, M., & Syed, J. (1999). An architecture for distributed enterprise data mining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1593, pp. 573–582). Springer Verlag. https://doi.org/10.1007/bfb0100618

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