Invention Grant
- Patent Title: Time series analysis using a clustering based symbolic representation
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Application No.: US15364681Application Date: 2016-11-30
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Publication No.: US10248713B2Publication Date: 2019-04-02
- Inventor: Paul Pallath , Ying Wu
- Applicant: Business Objects Software Ltd.
- Applicant Address: IE Dublin
- Assignee: Business Objects Software Ltd.
- Current Assignee: Business Objects Software Ltd.
- Current Assignee Address: IE Dublin
- Agency: Fish & Richardson P.C.
- Main IPC: G06F17/30
- IPC: G06F17/30 ; G06N99/00

Abstract:
Techniques are described for performing a time series analysis using a clustering based symbolic representation. Implementations employ a clustering based symbolic representation applied to time series data. In some implementations, the time series data is discretized into subsequences with regular time intervals, and symbols encoding the time intervals may be derived by performing clustering algorithms on the subsequences. In the new representation, a time series is transformed into a sequence of categorical values. The symbolic representation is suitable to perform time series classification and forecast with higher accuracy and greater efficiency compared to previously used techniques. Through use of the symbolic representation, a dimension reduction is applied to transform the time sequences to a feature space with lower dimensions. As output of such transformation, a new representation is obtained based on the original time series. This new reduced-dimension representation improves the efficiency of time series data mining and forecasting.
Public/Granted literature
- US20180150547A1 TIME SERIES ANALYSIS USING A CLUSTERING BASED SYMBOLIC REPRESENTATION Public/Granted day:2018-05-31
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