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Mining frequent itemsets in data streams has became one of the hottest research topics in data mining nowadays, recent algorithms that make use of definite error bound or probabilistic error bound, have relieved the temporal-spatial complexity at some extent. However, the introduction of unwanted sub-frequent itemsets, and the changes of itemsetspsila(More)
The vastness of ocean decides ocean observation data is spatially distributed and temporally continuous. As the ocean-observing means becomes much diverser, mass ocean observation data is accumulated. These data are heterogeneous and distributive, so the utilization of ocean observation data occurs many difficulties Focusing on heterogeneous and(More)
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