A Multi-Tier Architecture for High-Performance Data Mining

13 years 9 months ago
A Multi-Tier Architecture for High-Performance Data Mining
Data mining has been recognised as an essential element of decision support, which has increasingly become a focus of the database industry. Like all computationally expensive data analysis applications, for example Online Analytical Processing (OLAP), performance is a key factor for usefulness and acceptance in business. In the course of the CRITIKAL1 project (Client-Server Rule Induction Technology for Industrial Knowledge Acquisition from Large Databases), which is funded by the European Commission, several kinds of architectures for data mining were evaluated with a strong focus on high performance. Speci cally, the data mining techniques association rule discovery and decision tree induction were implemented into a prototype. We present the architecture developed by the CRITIKAL consortium and compare it to alternative architectures.
Ralf Rantzau, Holger Schwarz
Added 03 Aug 2010
Updated 03 Aug 2010
Type Conference
Year 1999
Where BTW
Authors Ralf Rantzau, Holger Schwarz
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