Systems and methods for structural clustering of time sequences
AssigneeIBM Corporation
InventorsVittorio Castelli, Michail Vlaschos, Philip Yu
Life of this patent
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Abstract
Arrangements and methods for performing structural clustering between different time series. Time series data relating to a plurality of time series is accepted, structural features relating to the time series data are ascertained, and at least one distance between different time series via employing the structural features is determined. The different time series may be partitioned into clusters based on the at least one distance, and/or the k closest matches to a given time series query based on the at least one distance may be returned.
Claims29
A method of performing structural clustering between different time series, said method comprising the steps of:
- accepting time series data relating to a plurality of time series;
- ascertaining structural features relating to the time series data;
- determining at least one distance between different time series via employing the structural features;
- and
- partitioning the different time series into clusters based on the at least one distance.
An apparatus for performing structural clustering between different time series, said apparatus comprising:
- an arrangement for accepting time series data relating to a plurality of time series;
- an arrangement for ascertaining structural features relating to the time series data;
- an arrangement for determining at least one distance between different time series via employing the structural features;
- and
- an arrangement for partitioning the different time series into clusters based on the at least one distance.
A program storage device readable by machine, tangibly embodying a program of instructions executed by the machine to perform method steps for performing structural clustering between different time series, said method comprising the steps of:
- accepting time series data relating to a plurality of time series;
- ascertaining structural features relating to the time series data;
- determining at least one distance between different time series via employing the structural features;
- and
- partitioning the different time series into clusters based on the at least one distance.
A method of quantifying the structural similarity between different time series, said method comprising the steps of:
- accepting time series data relating to a plurality of time series;
- ascertaining structural features relating to the time series data;
- determining at least one distance between different time series via employing the structural features;
- and
- returning the k closest matches to a given time series query based on the at least one distance.
An apparatus for quantifying the structural similarity between different time series, said apparatus comprising:
- an arrangement for accepting time series data relating to a plurality of time series;
- an arrangement for ascertaining structural features relating to the time series data;
- an arrangement for determining at least one distance between different time series via employing the structural features;
- and
- an arrangement for returning the k closest matches to a given time series query based on the at least one distance.
Dependencies are inferred from the claim text.