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Fast Subsequence Matching in Time-Series Databases

Fast Subsequence Matching in Time-Series Databases

陈重丶
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We present an efficient indexing method to locate ldimeneional subsequences within a collection of sequences,such that the subsequences match a given (query) pattern within a specified tolerance. The idea is to map each datasequence into a small set of multidimensional rectangles in feature space. Then, these rectangles can be readilyindexed using traditional spatial access methods, like theR*-tree [9]. In more deteil, we use a sliding window over the data sequence and extract its features; the result is a trail in feature space. We propose an efficient and effective algorithm to divide such trails into sub-trails, which are subsequently represented by their Minimum Bounding Rectangles (MBRs). We also examine queries of varying lengths, and we show how to handle each case efficiently.
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