Determining relevant information based on third party information and user interactions
A system for determining relevant information based on user interactions may include a processor configured to receive application data from one or more applications, the application data including features related to user activity from the one or more applications, the one or more application including applications local to the device that are stored in the memory and applications external to the device. The processor may be further configured to provide, using a machine learning (ML) model, a relevance score for each of one or more user interface (UI) elements based on each of the features. The processor may be further configured to sort one or more UI elements based on a ranking of the relevance scores. The processor may be further configured to provide, as output, the one or more UI elements based at least in part on the ranking.
1 . A device, comprising:
a memory; and
at least one processor configured to:
receive, by a background process and via one or more application programming interfaces, application data from one or more applications, the application data including features related to user activity from the one or more applications, wherein the one or more applications comprise at least one application local to the device and at least one application on another device;
provide, by the background process and using a machine learning (ML) model, a relevance score for each of one or more watch face user interface (UI) elements based on the features related to the user activity; and
display at least one of the one or more watch face UI elements based at least in part on the relevance scores.
2 . The device of claim 1 , wherein the relevance score is based at least in part on a sum of respective Gaussian curves.
3 . The device of claim 1 , wherein the relevance score is further based on a value indicating a likelihood that a user will click on or tap a particular watch face UI element.
4 . The device of claim 1 , wherein the features include a signal based on a location or time.
5 . The device of claim 1 , wherein the at least one processor is further configured to collect, by the background process and via the one or more application programming interfaces, the application data from multiple of the one or more applications.
6 . The device of claim 1 , wherein the features are included in different groups.
7 . The device of claim 6 , wherein the different groups include a group of features that are shared across the applications and a second group of features that are specific to a particular application.
8 . The device of claim 6 , wherein the device comprises a wearable electronic device and each watch face UI element is provided for display by the wearable electronic device in accordance with a ranking.
9 . The device of claim 1 , further comprising a display, wherein the at least one processor is configured to display, on the display, a scrollable list of the one or more watch face UI elements in an order determined based on sorting the one or more UI elements based on the relevance scores.
10 . A method comprising:
receiving, by a background process and via one or more application programming interfaces, application data from one or more applications, the application data including features related to user activity from the one or more applications, wherein the one or more applications comprise at least one local application and at least one external application;
providing, by the background process and using a machine learning (ML) model, a relevance score for each of one or more watch user interface (UI) elements based on the features related to the user activity; and
display at least one of the one or more watch UI elements based at least in part on the relevance scores.
11 . The method of claim 10 , wherein the features include a signal based on a location or time.
12 . The method of claim 10 , wherein receiving, by the background process and via the one or more application programming interfaces, the application data from the one or more applications comprises collecting, by the background process and via the one or more application programming interfaces, the application data from multiple of the one or more applications.
13 . The method of claim 10 , wherein the features are included in different groups.
14 . The method of claim 13 , wherein the different groups include a group of features that are shared across the applications and a second group of features that are specific to a particular application.
15 . The method of claim 10 , further comprising:
displaying, on a display, a scrollable list of the one or more watch face UI elements in an order determined based on sorting the one or more UI elements based on the relevance scores.
16 . A computer program product comprising code stored in a non-transitory computer-readable storage medium, the code comprising:
code to receive, by a background process and via one or more application programming interfaces, application data from one or more applications, the application data including one or more features related to user activity from the one or more applications, wherein the one or more applications comprise at least one local application and at least one external application;
code to provide, by the background process and using a machine learning (ML) model, a respective relevance score for each of one or more user interface (UI) elements based on the one or more features; and
code to display at least one of the one or more UI elements based at least in part on the respective relevance score for each of the one or more UI elements.
17 . The computer program product of claim 16 , wherein the features include a signal based on a location or time.
18 . The computer program product of claim 16 , wherein the code to receive, by a background process and via one or more application programming interfaces, application data from one or more applications, the application data comprises code to collect, by the background process and via the one or more application programming interfaces, the application data from multiple of the one or more applications.
19 . The computer program product of claim 16 , wherein the features are included in different groups.
20 . The computer program product of claim 19 , wherein the different groups include a group of features that are shared across the applications and a second group of features that are specific to a particular application.