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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© 1999 Springer-Verlag
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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: Sloot, P., Bubak, M., Hoekstra, A., Hertzberger, B. (eds) High-Performance Computing and Networking. HPCN-Europe 1999. Lecture Notes in Computer Science, vol 1593. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0100618
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DOI: https://doi.org/10.1007/BFb0100618
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