Systems and methods for selectively prefetching data

Patent metadata

Field	Value
Publication number	US-11720573-B2
Application number	US-202117378615-A
Country	US
Kind code	B2
Filing date	Jul 16, 2021
Priority date	Sep 29, 2020
Publication date	Aug 8, 2023
Grant date	Aug 8, 2023

Abstract

Systems and methods for intelligently pre-fetching data for input controls are disclosed. In particular, the disclosed systems and methods predict whether an input control is likely to be edited and only pre-fetches data for the input controls that have a high likelihood of being edited. This way, the presently disclosed systems and methods not only reduce latency in displaying recommended data results for input controls that are likely to be edited but also reduces the number of calls made to the backend server to retrieve the data as the data is not retrieved for all rendered input controls, but only the ones that are likely to be edited.

First claim

What is claimed is:

1. A computer-implemented method for operating a graphical user interface on a client device, the computer-implemented method comprising:
causing display of the graphical user interface on the client device, the graphical user interface including multiple input controls on the client device, each input control of the multiple input controls configured to display a respective list of suggested entries in response to a respective user input;
receiving, at a product platform server, a principal identifier associated with a user of the client device;
based on the principal identifier, identifying, at the product platform server, a set of historical interactions performed by the user with respect to the multiple input controls;
determining a likelihood that the user will select a particular input control based on a number of interactions with respect to an input control type identified in the set of historical interactions;
in accordance with the determined likelihood satisfying a criteria, causing a particular list of suggested entries for the particular input control to be transmitted from the product platform server to the client device; and
in response to a user selection of the particular input control, causing display of the particular list of suggested entries on the graphical user interface.

2. The computer-implemented method of claim 1 , wherein:
the set of historical interactions includes a count associated with a historical action performed by the user; and
determining the likelihood that the user will edit the particular input control further includes associating the historical action with the particular input control.

3. The computer-implemented method of claim 1 , wherein the particular list of suggested entries is pre-fetched by the product platform server for causing display on the graphical user interface.

4. The computer-implemented method of claim 1 , wherein at least one input control of the multiple input controls is not pre-fetched subsequent to causing display of the graphical user interface.

5. The computer-implemented method of claim 1 , wherein:
the criteria corresponds to a threshold level of a total assign ratio for the principal identifier; and
the total assign ratio corresponds to a ratio of a first number of times issues are assigned to the user and a second number of times issues are assigned to users other than the user.

6. The computer-implemented method of claim 1 , wherein determining the likelihood that the user will edit the particular input control further comprises:
obtaining contextual data associated with an object displayed on the graphical user interface; and
obtaining a predicted outcome for the particular input control using a machine learning model, the machine learning model trained using the set of historical interactions.

7. The computer-implemented method of claim 1 , wherein the particular input control is at least one of an assign input control, a mention input control, or a tag input control.

8. The computer-implemented method of claim 1 , further comprising processing an additional input control of the multiple input controls to determine an additional likelihood that the user will edit the additional input control.

9. A method for operating a graphical user interface for an issue of an issue tracking system, the method comprising:
causing display of issue data corresponding to the issue tracked by the issue tracking system in the graphical user interface on a client device, the graphical user interface including multiple input controls and each input control of the multiple input controls configured to display a respective list of suggested entries in response to a respective user input;
identifying a set of historical actions associated with a user of the client device, the user of the client device identified based on a principal identifier received from the client device;
determining a likelihood that the user will select a particular input control based on a number of interactions with respect to an input control type of a particular input control of multiple input controls identified in the set of historical interactions;
in accordance with the determined likelihood, determining and transmitting suggested entries for the particular input control of the input control type to the client device; and
in response to a user selection of the particular input control, causing display of the suggested entries corresponding to the particular input control.

10. The method of claim 9 , wherein the set of historical actions corresponds to a number of times each input control of the multiple input controls was selected for editing by the user associated with the principal identifier.

11. The method of claim 9 , wherein:
the input control type corresponds to an issue assignment control; and
the input control is an assignee selection control for the issue tracked by the issue tracking system.

12. The method of claim 9 , wherein the likelihood is identified using a machine learning model trained using the set of historical actions.

13. The method of claim 9 , wherein additional suggested entries are not pre-fetched prior to an additional user selection of at least one additional input control.

14. The method of claim 9 , wherein the set of historical actions indicates at least one of a frequency of assign events, a creator of the issue, or an assignor of the issue.

15. The method of claim 9 , wherein:
the suggested entries received at the client device are stored in a local cache of the client device; and
the suggested entries are fetched from the local cache in response to the user selection of the input control.

16. A computer system comprising:
a processor; and
a non-transitory computer readable medium storing sequences of instructions which, when executed by the processor, cause the processor to:
cause display of a graphical user interface on a client device, the graphical user interface including multiple input controls on a client device, each input control of the multiple input controls configured to display a respective list of suggested entries in response to a respective user input;
receive a recommendation request for pre-fetching data for an input control of the multiple input controls associated with an object displayed on the graphical user interface, the recommendation request including an input control type identifier and a principal identifier of a user of the client device;
based on the recommendation request, identify a set of historical interactions performed by the user with respect to the multiple input controls;
determine a likelihood that the user of the client device will select and edit the input control of the multiple input controls associated with the object displayed on the graphical user interface in accordance with a number of interactions with respect to the input control identified in the set of historical interactions; and

in accordance with the likelihood satisfying a criteria and in response to a user input of the input control, cause rendering and display of a list of suggested entries for the input control of the multiple input controls associated with the object displayed on the graphical user interface.

17. The computer system of claim 16 , wherein:
the recommendation request further includes an object identifier; and
the likelihood that the user will select and edit the input control further comprises:
determining whether the object is currently assigned based on the object identifier;
determining whether a status of the object is current

Assignees

• Atlassian Pty Ltd
• Atlassian Inc
• Atlassian Us Inc

Inventors

• Wondo Addo
• Saad Ahmed
• Sims Geoff
• Atanasov Penyo
• Hamid Shihab Hassan
• Awadhwal Gaurav
• Rho Edison
• De Souza Jr Gilmar Jose Alves

Classifications

• G06F16/24575 Primary

  using context · CPC title

• G06N20/00

  Machine learning · CPC title

• H04L67/5681

  Pre-fetching or pre-delivering data based on network characteristics · CPC title

• G06F3/04842

  Selection of displayed objects or displayed text elements (G06F3/0482 takes precedence) · CPC title

• G06F16/9574 Primary

  of access to content, e.g. by caching · CPC title