Efficient processing of subsequence matching with the euclidean metric in time-series databases

Abstrocr In this paper, we discuss eflicient processing of subsequence matching in time-series databases. We first point out the performance problems of Dual-Match, a previous subsequence matching method, and then propose a new one resolving them. The propwed method starts with a new attempt that observes the index search occurred in subsequence matching as a windowjoin, a kind of the spatial-join. For effective processing of the window-join, we build an R*-tree for query window points within the main memory on the ny. We also propose a novel algorithm for eflicient processing of the join on the two R'-trees; one for query window points residing in the main memory and the other for data window points residing in the disk. Performance evaluation via experiments shows the superiority of the proposed method compared with DualMatch.

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