Departments of Computer Sciences|University of Wisconsin
被引用26|浏览4
摘要
We present two heuristics for speeding up a time series alignment algorithm that is related to dynamic time warping (DTW). In previous work, we developed our multisegment alignment algorithm to answer similarity queries for toxicogenomic time-series data. Our multisegment algorithm returns more accurate alignments than DTW at the cost of time complexity; the multisegment algorithm is O(n(5)) whereas DTW is O(n(2)). The first heuristic we present speeds up our algorithm by a constant factor by restricting alignments to a cone shape in alignment space. The second heuristic restricts the alignments considered to those near one returned by a DTW-like method. This heuristic adjusts the time complexity to O(n(3)). Importantly, neither heuristic results in a loss in accuracy.
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关键词
Dynamic Time Warping,Dimensionality Reduction,Feature Extraction