Comparing data series associated with two systems to identify hidden similarities between them
First Claim
1. A method comprising:
- obtaining a first data series and a second data series, wherein the first data series being associated with values of a parameter sampled from a first system, wherein the second data series being associated with values of the parameter sampled from a second system;
calculating a correlation level between the first and second data series;
in response to the correlation level being below a predetermined threshold, processing the first and second data series by;
repeatedly selecting a transformation from a transformation repository, applying the transformation to the second data series, and computing the correlation level of the first data series and the transformed second data series;
selecting, based on the computed correlation levels, the transformation of the plurality of transformations that yields a correlation level above the predetermined threshold; and
providing a recommendation of a modification to the second system based on the selected transformation;
wherein the plurality of transformations are associated with an order, and wherein said selecting the transformation from the plurality of transformations is performed based on the order, andreordering the transformations in the transformation repository to reduce computational intensity of the repeated applications;
wherein at least one of said calculating, said applying and said providing is performed by a processor.
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Abstract
A method that includes: sampling a plurality of parameters associated with a first and a second system to yield a first and a second set of data series, respectively, each data series being associated with samples of a respective parameter; applying, for each two respective data series, a transformation associated with a specified order selected from a plurality of ordered transformations, such that the selected transformation is applied repeatedly to at least one of the two respective data series, wherein, in each repeated application, the transformation is assigned with a different value of a transformation parameter; determining, for each parameter, a one of the plurality of transformation parameters for which the correlation level of the two respective time series is above a specified value; and repeating the applying and the determining with a transformation that is associated with a higher order of the ordered transformations.
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Citations
18 Claims
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1. A method comprising:
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obtaining a first data series and a second data series, wherein the first data series being associated with values of a parameter sampled from a first system, wherein the second data series being associated with values of the parameter sampled from a second system; calculating a correlation level between the first and second data series; in response to the correlation level being below a predetermined threshold, processing the first and second data series by; repeatedly selecting a transformation from a transformation repository, applying the transformation to the second data series, and computing the correlation level of the first data series and the transformed second data series; selecting, based on the computed correlation levels, the transformation of the plurality of transformations that yields a correlation level above the predetermined threshold; and providing a recommendation of a modification to the second system based on the selected transformation; wherein the plurality of transformations are associated with an order, and wherein said selecting the transformation from the plurality of transformations is performed based on the order, and reordering the transformations in the transformation repository to reduce computational intensity of the repeated applications; wherein at least one of said calculating, said applying and said providing is performed by a processor. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A computer program product comprising a non-transitory computer readable medium having instructions retained thereon, which instructions, when provided to a processor, cause the processor to:
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obtain a first data series and a second data series, wherein the first data series being associated with values of a parameter sampled from a first system, wherein the second data series being associated with values of the parameter sampled from a second system; calculate a correlation level between the first and second data series; in response to the correlation level being below a predetermined threshold, process the first and second data series by; repeatedly selecting a transformation from a transformation repository, applying the transformation to the second data series, and computing the correlation level of the first data series and the transformed second data series; selecting, based on the computed correlation levels, the transformation of the plurality of transformations that yields a correlation level above the predetermined threshold; and providing a recommendation of a modification to the second system based on the selected transformation; wherein the plurality of transformations are associated with an order, and wherein said selecting the transformation from the plurality of transformations is performed based on the order, and reordering the transformations in the transformation repository to reduce computational intensity of the repeated applications.
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18. A computerized apparatus comprising a processor coupled to a memory, wherein said processor is configured to:
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obtain a first data series and a second data series, wherein the first data series being associated with values of a parameter sampled from a first system, wherein the second data series being associated with values of the parameter sampled from a second system; calculate a correlation level between the first and second data series; in response to the correlation level being below a predetermined threshold, process the first and second data series by; repeatedly selecting a transformation from a transformation repository, applying the transformation to the second data series, and computing the correlation level of the first data series and the transformed second data series; selecting, based on the computed correlation levels, the transformation of the plurality of transformations that yields a correlation level above the predetermined threshold; and providing a recommendation of a modification to the second system based on the selected transformation; wherein the plurality of transformations are associated with an order, and wherein said selecting the transformation from the plurality of transformations is performed based on the order, and reordering the transformations in the transformation repository to reduce computational intensity of the repeated applications.
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Specification