Providing suggestions within a document

• US 9,959,296 B1
• Filed: 05/12/2014
• Issued: 05/01/2018
• Est. Priority Date: 05/12/2014
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google LLC (Alphabet Inc.)
• Inventors: Gubin, Maxim, Dauber, Kenneth W., Sung, Sangsoo, Bharat, Krishna
• Primary Examiner(s): Hoang, Son T
• Application Number:
  US14/275,333
• Time in Patent Office: 1,450 Days
• Field of Search: None
• CPC Class Codes: G06F 16/219 Managing data history or versioning querying versioned data G06F16/2474; querying temporal data G06F16/2477
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases
• CPC Class Codes: G06F 16/93 Document management systems

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing suggestions within a document. In one aspect, a method includes obtaining textual input provided to a document editing application by a user device, the textual input being provided to the document editing application for inclusion in a document; identifying performance measures associated with the current editing session for the document, each performance measure being based on session data obtained from the user device during a document editing session, the session data being for the textual input and prior text that was included in the document prior to the textual input; providing the performance measures as input to a suggestion model that was trained using historical performance measures identified in performance logs for historical document editing sessions of users; and throttling textual suggestions during the current editing session based on the output of the suggestion model.

Claims

1. A method implemented by data processing apparatus, the method comprising:

obtaining, during a current editing session, textual input provided to a document editing application by a user associated with a user device, the textual input being provided to the document editing application for inclusion in a document;

receiving textual suggestions from a suggestion model based on the obtained textual input, each textual suggestion comprising one or more words to be suggested for inclusion in the document, each textual suggestion having a confidence score;

providing, during the current editing session and not to the user, respective textual suggestions having confidence scores above a current threshold value;

identifying, during the current editing session, one or more performance measures associated with the current editing session for the document, each performance measure being at least one of a typing speed of the user or a latency of the user device based on session data obtained during a document editing session, the session data being for the obtained textual input and prior texts included in the document prior to the obtained textual input;

providing the one or more performance measures as input to the suggestion model that was trained using historical performance measures identified in performance logs for a plurality of historical document editing sessions of a plurality of users prior to the current editing session;

generating a modified threshold value based on the inputted one or more performance measures, the modified threshold value different from the current threshold value; and

throttling the textual suggestions during the current editing session by providing, during the current editing session and to the user, at least one of the respective textual suggestions having a confidence score above the modified threshold value.

2. The method of claim 1, further comprising:

training the suggestion model based on the historical performance measures and historical suggestions included in the performance logs.

3. The method of claim 2, wherein the training the suggestion model comprises:

determining, based on the historical performance measures and the historical suggestions included in the performance logs, a relation between the user'"'"'s typing speed and a rate of historical suggestion acceptance; and

training the suggestion model based on the determined relation.

4. The method of claim 2, wherein the training the suggestion model comprises:

determining, based on the historical performance measures and the historical suggestions included in the performance logs, a relation between the user device'"'"'s latency and a rate of historical suggestion acceptance; and

training the suggestion model based on the determined relation.

5. The method of claim 2, wherein the training the suggestion model comprises:

determining, based on the historical performance measures and the historical suggestions included in the performance logs, a relation between a suggestion confidence score and a rate of historical suggestion acceptance; and

training the suggestion model based on the determined relation.

6. The method of claim 1, wherein the one or more performance measures further comprise:

a rate of suggestion acceptance that specifies a rate of acceptance for previous suggestions that were provided during the plurality of historical document editing sessions.

7. The method of claim 1, wherein:

the one or more performance measures further comprise a rate of acceptance for previous suggestions that were provided during the plurality of document editing sessions; and

the modified threshold provided by the suggestion model depends on the rate of acceptance for previous suggestions.

8. The method of claim 1, wherein:

the user device'"'"'s latency specifies a communications delay between the user device and the document editing application;

the threshold values of the suggestion model is associated with a latency threshold; and

the throttling textual suggestions comprises providing textual suggestions to the user device only in response to the user device latency meeting the latency threshold.

9. The method of claim 1, wherein:

the user'"'"'s typing speed specifies a speed at which the user device provides the obtained textual input to the document editing application;

the threshold values of the suggestion model is associated with a typing speed threshold; and

the throttling textual suggestions comprises providing the textual suggestion to the user device only in response to the user'"'"'s typing speed meeting the typing speed threshold.

10. The method of claim 1, wherein the document editing application is one of a plurality of document editing applications, and the suggestion model was trained using respective historical performance measures identified in respective performance logs for the document editing application.

11. The method of claim 1, wherein the document editing session from which session data is obtained is the current editing session.

12. A system comprising:

one or more data processing apparatus implemented at least partially by hardware; and

a data storage device storing instructions that, when executed by the one or more data processing apparatus, cause the one or more data processing apparatus to perform operations comprising;

obtaining, during a current editing session, textual input provided to a document editing application by a user associated with a user device, the textual input being provided to the document editing application for inclusion in a document;

receiving textual suggestions from a suggestion model based on the obtained textual input each textual suggestion comprising one or more words to be suggested for inclusion in the document, each textual suggestion having a confidence score;

providing, during the current editing session and not to the user, respective textual suggestions having confidence scores above a current threshold value;

identifying, during the current editing session, one or more performance measures associated with the current editing session for the document, each performance measure being at least one of a typing speed of the user or a latency of the user device based on session data obtained during a document editing session, the session data being for the obtained textual input and prior texts included in the document prior to the obtained textual input;

providing the one or more performance measures as input to the suggestion model that was trained using historical performance measures identified in performance logs for a plurality of historical document editing sessions of a plurality of users prior to the current editing session;

generating a modified threshold value based on the inputted one or more performance measures, the modified threshold value different from the current threshold value; and

throttling the textual suggestions during the current editing session by providing, during the current editing session and to the user at least one of the respective textual suggestions having a confidence score above the modified threshold value.

13. The system of claim 12, wherein the operations further comprise:

training the suggestion model based on the historical performance measures and historical suggestions included in the performance logs.

14. The system of claim 13, wherein the training the suggestion model comprises:

determining, based on the historical performance measures and the historical suggestions included in the performance logs, a relation between the user'"'"'s typing speed and a rate of historical suggestion acceptance; and

training the suggestion model based on the determined relation.

15. The system of claim 13, wherein the training the suggestion model comprises:

determining, based on the historical performance measures and the historical suggestions included in the performance logs, a relation between the user device'"'"'s latency and a rate of historical suggestion acceptance; and

training the suggestion model based on the determined relation.

16. The system of claim 13, wherein the training the suggestion model comprises:

determining, based on the historical performance measures and the historical suggestions included in the performance logs, a relation between a suggestion confidence score and a rate of historical suggestion acceptance; and

training the suggestion model based on the determined relation.

17. The system of claim 12, wherein the one or more performance measures further comprise:

a rate of suggestion acceptance that specifies a rate of acceptance for previous suggestions that were provided during the plurality of historical document editing sessions.

18. A non-transitory computer-readable medium comprising instructions that, when executed by one or more data processing apparatus, cause the one or more data processing apparatus to perform operations comprising:

obtaining, during a current editing session, textual input provided to a document editing application by a user associated with a user device, the textual input being provided to the document editing application for inclusion in a document;

receiving textual suggestions from a suggestion model based on the obtained textual input, each textual suggestion comprising one or more words to be suggested for inclusion in the document, each textual suggestion having a confidence score;

providing, during the current editing session and not to the user, respective textual suggestions having confidence scores above a current threshold value;

identifying, during the current editing session, one or more performance measures associated with the current editing session for the document, each performance measure being at least one of a typing speed of the user or a latency of the user device based on session data obtained during a document editing session, the session data being for the obtained textual input and prior texts included in the document prior to the obtained textual input;

providing the one or more performance measures as input to the suggestion model that was trained using historical performance measures identified in performance logs for a plurality of historical document editing sessions of a plurality of users prior to the current editing session;

generating a modified threshold value based on the inputted one or more performance measures, the modified threshold value different from the current threshold value; and

throttling the textual suggestions during the current editing session by providing, during the current editing session and to the user at least one of the respective textual suggestions having a confidence score above the modified threshold value.