Predictive model application programming interface

• US 8,229,864 B1
• Filed: 09/30/2011
• Issued: 07/24/2012
• Est. Priority Date: 05/06/2011
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Lin, Wei-Hao, Green, Travis H. K., Kaplow, Robert, Fu, Gang, Mann, Gideon S.
• Primary Examiner(s): Holmes, Michael B
• Application Number:
  US13/250,394
• Time in Patent Office: 298 Days
• Field of Search: 706/11
• US Class Current: 706/11
• CPC Class Codes: G06F 40/18 of spreadsheets form-filling G06F40/174
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for utilizing predictive models from an application scripting language.

Claims

1. A computer-implemented method, the method comprising:

obtaining a plurality of scripts each having been received from a different client wherein each script contains a reference to one or more interactive fields of a graphical user interface presented on the client, and wherein the script also contains a reference to a distinct predictive model;

executing each script by a script engine wherein executing the script causes data of the interactive fields referenced by the script to be provided as input to the respective predictive model referenced by the script, and wherein at least two of the scripts are executed in parallel on different sets of one or more computing devices of a plurality of computing devices;

processing each provided input data by the respective predictive model wherein the processing includes providing output of the respective predictive model to the script engine from which the input data was provided, and wherein each respective predictive model executes on a different set of one or more computing devices of the plurality of computing devices; and

wherein executing each script includes providing the output of each respective predictive model to the respective client for presenting in the graphical user interface of the respective client.

2. The method of claim 1 wherein a portion of the execution of the at least two scripts occurs at a same time.

3. The method of claim 1 wherein processing each provided input data by the respective predictive model includes training the predictive model with the input data.

4. The method of claim 1 wherein processing each provided input data by the respective predictive model includes determining one or more predictions based on the input data.

5. The method of claim 1 wherein the output is a prediction.

6. The method of claim 1 wherein the output is a training status for the respective predictive model.

7. The method of claim 1 wherein the graphical user interface presented on the client is for a spreadsheet application, a word processor application, or an email application.

8. The method of claim 1 wherein the one or more interactive fields are user-editable fields presented in the graphical user interface.

9. A system comprising:

a plurality of first computing devices configured to obtain a plurality of scripts each having been received from a different client wherein each script contains a reference to one or more interactive fields of a graphical user interface presented on the client, and wherein the script also contains a reference to a distinct predictive model;

a plurality of second computing devices configured to execute each script using a script engine wherein executing the script causes data of the interactive fields referenced by the script to be provided as input to the respective predictive model referenced by the script, and wherein at least two of the scripts are executed in parallel on different sets of one or more computing devices of the second computing devices;

a plurality of third computing devices configured to process the provided input data by the respective predictive model wherein the processing includes providing output of the respective predictive model to the script engine from which the input data was provided, and wherein each respective predictive model executes on a different set of one or more computing devices of the third computing devices; and

wherein executing each script includes providing the output of each respective predictive model to the respective client for presenting in the graphical user interface of the respective client.

10. The system of claim 9 wherein a portion of the execution of the at least two scripts occurs at a same time.

11. The system of claim 9 wherein processing each provided input data by the respective predictive model includes training the predictive model with the input data.

12. The system of claim 9 wherein processing each provided input data by the respective predictive model includes determining one or more predictions based on the input data.

13. The system of claim 9 wherein the output is a prediction.

14. The system of claim 9 wherein the output is a training status for the respective predictive model.

15. The system of claim 9 wherein the graphical user interface presented on the client is for a spreadsheet application, a word processor application, or an email application.

16. The system of claim 9 wherein the one or more interactive fields are user-editable fields presented in the graphical user interface.

17. A storage medium have instructions stored thereon that, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising:

obtaining a plurality of scripts each having been received from a different client wherein each script contains a reference to one or more interactive fields of a graphical user interface presented on the client, and wherein the script also contains a reference to a distinct predictive model;

executing each script by a script engine wherein executing the script causes data of the interactive fields referenced by the script to be provided as input to the respective predictive model referenced by the script, and wherein at least two of the scripts are executed in parallel on different sets of one or more computing devices of a plurality of computing devices;

processing each provided input data by the respective predictive model wherein the processing includes providing output of the respective predictive model to the script engine from which the input data was provided, and wherein each respective predictive model executes on a different set of one or more computing devices of the plurality of computing devices; and

wherein executing each script includes providing the output of each respective predictive model to the respective client for presenting in the graphical user interface of the respective client.

18. The storage medium of claim 17 wherein a portion of the execution of the at least two scripts occurs at a same time.

19. The storage medium of claim 17 wherein processing each provided input data by the respective predictive model includes training the predictive model with the input data.

20. The storage medium of claim 17 wherein processing each provided input data by the respective predictive model includes determining one or more predictions based on the input data.

21. The storage medium of claim 17 wherein the output is a prediction.

22. The storage medium of claim 17 wherein the output is a training status for the respective predictive model.

23. The storage medium of claim 17 wherein the graphical user interface presented on the client is for a spreadsheet application, a word processor application, or an email application.

24. The storage medium of claim 17 wherein the one or more interactive fields are user-editable fields presented in the graphical user interface.