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SIMILAR TIME SERIES DATA COMPUTING APPARATUS, SIMILAR TIME SERIES DATA COMPUTING METHOD AND SIMILAR TIME SERIES DATA COMPUTING PROGRAM

机译:类似时间序列数据计算装置,类似时间序列数据计算方法和类似时间序列数据计算程序

摘要

PPROBLEM TO BE SOLVED: To reduce computing costs in determining the similarity of time series data. PSOLUTION: A refining part 3 refines time series data by using a multi-dimensional index structure, and a similarity determination part 4 calculates a distance between dimensionally compressed time series data, and when the distance is a predetermined threshold or less, the similarity determination part 4 decides that the time series data are similar. Thus, it is possible to reduce computing costs by determining similarity by using the dimensionally compressed time series data. Also, it is possible to obtain all correct similarity determination results by dimensionally compressing the time series data so that the distance between the time series data before dimensional compression can be the distance between the dimensionally compressed time series data or less. Furthermore, it is possible to obtain all correct similarity determination results without omission by similarity determination by using the time series data before dimensional compression when the similarity determination using the dimensionally compressed time series data is difficult. PCOPYRIGHT: (C)2006,JPO&NCIPI
机译:

要解决的问题:减少确定时间序列数据的相似性时的计算成本。

解决方案:提炼部分3通过使用多维索引结构提炼时间序列数据,相似性确定部分4计算维度压缩的时间序列数据之间的距离,并且当该距离为预定阈值或更小时,相似度确定部分4确定时间序列数据相似。因此,可以通过使用维度压缩的时间序列数据来确定相似性来降低计算成本。而且,可以通过对时间序列数据进行维度压缩来获得所有正确的相似性确定结果,使得维度压缩之前的时间序列数据之间的距离可以为维度压缩后的时间序列数据之间的距离或更小。此外,当难以使用尺寸压缩的时间序列数据进行相似度确定时,通过使用尺寸压缩之前的时间序列数据,可以通过相似度确定获得所有正确的相似度确定结果而不遗漏。

版权:(C)2006,JPO&NCIPI

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