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Design and Analysis of a Reconfigurable Platform for Frequent Pattern Mining.
- Source :
-
IEEE Transactions on Parallel & Distributed Systems . Sep2011, Vol. 22 Issue 9, p1497-1505. 0p. - Publication Year :
- 2011
-
Abstract
- Frequent pattern mining algorithms are designed to find commonly occurring sets in databases. This class of algorithms is typically very memory intensive, leading to prohibitive runtimes on large databases. A class of reconfigurable architectures has been recently developed that have shown promise in accelerating some data mining applications. In this paper, we propose a new architecture for frequent pattern mining based on a systolic tree structure. The goal of this architecture is to mimic the internal memory layout of the original pattern mining software algorithm while achieving a higher throughput. We provide a detailed analysis of the area and performance requirements of our systolic tree-based architecture, and show that our reconfigurable platform is faster than the original software algorithm for mining long frequent patterns. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10459219
- Volume :
- 22
- Issue :
- 9
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Parallel & Distributed Systems
- Publication Type :
- Academic Journal
- Accession number :
- 63244977
- Full Text :
- https://doi.org/10.1109/TPDS.2011.34