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US Patent 10037305 Computer-implemented systems and methods for time series exploration

Patent 10037305 was granted and assigned to Sas (company) on July, 2018 by the United States Patent and Trademark Office.

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Patent
Patent
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Patent attributes

Patent Applicant
Sas (company)
Sas (company)
0
Current Assignee
Sas (company)
Sas (company)
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
100373050
Patent Inventor Names
Sujatha Pothireddy0
Edward Tilden Blair0
Jerzy Michal Brzezicki0
Michael James Leonard0
Udo V. Sglavo0
Date of Patent
July 31, 2018
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Patent Application Number
158900190
Date Filed
February 6, 2018
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Patent Citations Received
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US Patent 11500829 Adapting time series database schema
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US Patent D898059 Display screen or portion thereof with graphical user interface
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US Patent D898060 Display screen or portion thereof with graphical user interface
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US Patent 10795935 Automated generation of job flow definitions
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US Patent 10977336 System and method of pre-processing discrete datasets for use in machine learning
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US Patent 11609885 Time series database comprising a plurality of time series database schemas
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US Patent 11321284 Adapting time series database schema
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US Patent 11762853 Querying a variably partitioned time series database
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Patent Primary Examiner
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William Titcomb
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Patent abstract

Systems and methods are provided for analyzing unstructured time stamped data. A distribution of time-stamped data is analyzed to identify a plurality of potential time series data hierarchies for structuring the data. An analysis of a potential time series data hierarchy may be performed. The analysis of the potential time series data hierarchies may include determining an optimal time series frequency and a data sufficiency metric for each of the potential time series data hierarchies. One of the potential time series data hierarchies may be selected based on a comparison of the data sufficiency metrics. Multiple time series may be derived in a single-read pass according to the selected time series data hierarchy. A time series forecast corresponding to at least one of the derived time series may be generated.

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