Heuristic scheduling of concurrent data mining queries

Authors:
Marek Wojciechowski;Maciej Zakrzewicz
Affiliations:
Institute of Computing Science, Poznan University of Technology, Poznan, Poland;Institute of Computing Science, Poznan University of Technology, Poznan, Poland
Venue:
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
Year:
2005

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Abstract

Execution cost of batched data mining queries can be reduced by integrating their I/O steps. Due to memory limitations, not all data mining queries in a batch can be executed together. In this paper we introduce a heuristic algorithm called CCFull,which suboptimally schedules the data mining queries into a number of execution phases. The algorithm significantly outperforms the optimal approach while providing a very good accuracy.