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10

CORR
2004
Springer

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Mining Frequent Itemsets from Secondary Memory

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Mining Frequent Itemsets from Secondary Memory

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Mining frequent itemsets is at the core of mining association rules, and is by now quite well understood algorithmically for main memory databases. In this paper, we investigate approaches to mining frequent itemsets when the database or the data structures used in the mining are too large to fit in main memory. Experimental results show that our techniques reduce the required disk accesses by orders of magnitude, and enable truly scalable data mining.

Gösta Grahne, Jianfei Zhu

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CORR 2004 | Education | Frequent Itemsets | Main Memory | Mining |

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Added	17 Dec 2010
Updated	17 Dec 2010
Type	Journal
Year	2004
Where	CORR
Authors	Gösta Grahne, Jianfei Zhu

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