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IEEE Transactions on Knowledge and Data Engineering
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Parallel mining of association rules

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Abstract

We consider the problem of mining association rules on a shared-nothing multiprocessor. We present three algorithms that explore a spectrum of trade-offs between computation, communication, memory usage, synchronization, and the use of problem-specific information. The best algorithm exhibits near perfect scaleup behavior, yet requires only minimal overhead compared to the current best serial algorithm. ©1996 IEEE.

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IEEE Transactions on Knowledge and Data Engineering

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