Patents by Inventor Udo V. SGLAVO
Udo V. SGLAVO has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 10037305Abstract: 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.Type: GrantFiled: February 6, 2018Date of Patent: July 31, 2018Assignee: SAS INSTITUTE INC.Inventors: Michael James Leonard, Edward Tilden Blair, Jerzy Michal Brzezicki, Udo V. Sglavo, Sujatha Pothireddy
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Patent number: 10025753Abstract: 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.Type: GrantFiled: February 6, 2018Date of Patent: July 17, 2018Assignee: SAS INSTITUTE INC.Inventors: Michael James Leonard, Edward Tilden Blair, Jerzy Michal Brzezicki, Udo V. Sglavo, Sujatha Pothireddy
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Publication number: 20180157620Abstract: 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.Type: ApplicationFiled: February 6, 2018Publication date: June 7, 2018Applicant: SAS Institute Inc.Inventors: Michael James Leonard, Edward Tilden Blair, Jerzy Michal Brzezicki, Udo V. Sglavo, Sujatha Pothireddy
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Publication number: 20180157619Abstract: 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.Type: ApplicationFiled: February 6, 2018Publication date: June 7, 2018Applicant: SAS Institute Inc.Inventors: Michael James Leonard, Edward Tilden Blair, Jerzy Michal Brzezicki, Udo V. Sglavo, Sujatha Pothireddy
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Patent number: 9916282Abstract: 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.Type: GrantFiled: June 10, 2015Date of Patent: March 13, 2018Assignee: SAS INSTITUTE INC.Inventors: Michael James Leonard, Edward Tilden Blair, Jerzy Michal Brzezicki, Udo V. Sglavo, Ranbir Singh Tomar, Kannukuzhiyil Kurien Kurien, Sujatha Pothireddy, Rajib Nath, Vilochan Suresh Muley
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Publication number: 20150278153Abstract: 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.Type: ApplicationFiled: June 10, 2015Publication date: October 1, 2015Inventors: Michael James Leonard, Edward Tilden Blair, Jerzy Michal Brzezicki, Udo V. Sglavo, Ranbir Singh Tomar, Kannukuzhiyil Kurien Kurien, Sujatha Pothireddy, Rajib Nath, Vilochan Suresh Muley
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Patent number: 9087306Abstract: Systems and methods are provided for analyzing unstructured time stamped data of a physical process in order to generate structured hierarchical data for a hierarchical time series analysis application. A plurality of time series analysis functions are selected from a functions repository. Distributions of time stamped unstructured data are analyzed to identify a plurality of potential hierarchical structures for the unstructured data with respect to the selected time series analysis functions.Type: GrantFiled: July 13, 2012Date of Patent: July 21, 2015Assignee: SAS Institute Inc.Inventors: Michael James Leonard, Edward Tilden Blair, Jerzy Michal Brzezicki, Udo V. Sglavo, Ranbir Singh Tomar, Kannukuzhiyil Kurien Kurien, Sujatha Pothireddy, Rajib Nath, Vilochan Suresh Muley
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Patent number: 9037998Abstract: Systems and methods are provided for analyzing unstructured time stamped data. A first series of user display screens are provided, where the first series of user display screens are configured to be displayed in a step-wise manner so that a user can specify a first approach through a series of predetermined steps on how the unstructured data is to be structured. A second series of user display screens are provided, where the second series of user display screens are configured to be displayed in a step-wise manner so that the user can specify a second approach through the series of predetermined steps on how the unstructured data is to be structured. Tracking data enables alternate viewing of the first and second approach to facilitate a decision whether to format the unstructured time stamped data according to the first approach or the second approach.Type: GrantFiled: July 18, 2012Date of Patent: May 19, 2015Assignee: SAS Institute Inc.Inventors: Michael James Leonard, Michael Ryan Chipley, Kshitija Ambulgekar, Sagar Arun Mainkar, Ashwini Bhalchandra Dixit, Sarika Shrotriya, Udo V. Sglavo, Dinesh P. Apte
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Publication number: 20140019909Abstract: Systems and methods are provided for analyzing unstructured time stamped data. A first series of user display screens are provided, where the first series of user display screens are configured to be displayed in a step-wise manner so that a user can specify a first approach through a series of predetermined steps on how the unstructured data is to be structured. A second series of user display screens are provided, where the second series of user display screens are configured to be displayed in a step-wise manner so that the user can specify a second approach through the series of predetermined steps on how the unstructured data is to be structured. Tracking data enables alternate viewing of the first and second approach to facilitate a decision whether to format the unstructured time stamped data according to the first approach or the second approach.Type: ApplicationFiled: July 18, 2012Publication date: January 16, 2014Inventors: Michael James Leonard, Michael Ryan Chipley, Kshitija Ambulgekar, Sagar Arun Mainkar, Ashwini Bhalchandra Dixit, Sarika Shrotriya, Udo V. Sglavo, Dinesh P. Apte
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Publication number: 20140019088Abstract: Systems and methods are provided for analyzing unstructured time stamped data of a physical process in order to generate structured hierarchical data for a hierarchical time series analysis application. A plurality of time series analysis functions are selected from a functions repository. Distributions of time stamped unstructured data are analyzed to identify a plurality of potential hierarchical structures for the unstructured data with respect to the selected time series analysis functions.Type: ApplicationFiled: July 13, 2012Publication date: January 16, 2014Inventors: Michael James LEONARD, Edward Tilden BLAIR, Jerzy Michal BRZEZICKI, Udo V. SGLAVO, Ranbir Singh TOMAR, Kannukuzhiyil Kurien KURIEN, Sujatha POTHIREDDY, Rajib NATH, Vilochan Suresh MULEY