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Linear Detrending Subsequence Matching in Time-Series Databases

机译:时间序列数据库中的线性去趋势子序列匹配

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Every time-series has its own linear trend, the directionality of a time-series, and removing the linear trend is crucial to get more intuitive matching results. Supporting the linear detrending in subsequence matching is a challenging problem due to the huge number of all possible subsequences. In this paper we define this problem as the linear detrending subsequence matching and propose its efficient index-based solution. To this end, we first present a notion of LD-windows (LD means linear detrending). Using the LD-windows we then present a lower bounding theorem for the index-based matching solution and show its correctness. We next propose the index building and subsequence matching algorithms. We finally show the superiority of the index-based solution.
机译:每个时间序列都有自己的线性趋势,时间序列的方向性,而删除线性趋势对于获得更直观的匹配结果至关重要。由于所有可能的子序列数量众多,在子序列匹配中支持线性去趋势是一个具有挑战性的问题。在本文中,我们将这个问题定义为线性去趋势子序列匹配,并提出其有效的基于索引的解决方案。为此,我们首先提出 LD窗口的概念(LD表示线性趋势)。然后,使用LD窗口为基于索引的匹配解决方案提出一个下界定理,并证明其正确性。接下来,我们提出索引构建和子序列匹配算法。我们最终展示了基于索引的解决方案的优越性。

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