We propose the design of a data management abstraction level to implement a full set of parallel KDD applications with minimal performance overhead and greater scalability than conventional DBMS, providing a high-level parallel API to be exploited by parallel and out-of-core data mining algorithms. We describe an existing prototype and report examples and first test results with mining algorithms.
A parallel data management layer for data mining
Coppola M;
2006
Abstract
We propose the design of a data management abstraction level to implement a full set of parallel KDD applications with minimal performance overhead and greater scalability than conventional DBMS, providing a high-level parallel API to be exploited by parallel and out-of-core data mining algorithms. We describe an existing prototype and report examples and first test results with mining algorithms.File in questo prodotto:
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