Publication Date:
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.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Data management; Parallel I/O; Parallel data mining; Knowledge Discovery in Databases
List of contributors: