Granted Patent B2

US 12,229,167 · App. 18/316,929 · Granted Feb 18, 2025

Inventors: Anubhav Malhotra (Sunnyvale, CA); John M. Hörnkvist (Cupertino, CA)

Assignee: Apple Inc.

G06F16/285G06F16/2228G06F16/248G06F16/951

Abstract

Claims (62)

1. A non-transitory machine-readable medium having executable instructions to cause one or more processing units to perform a method to index content from an application on an electronic device, the method comprising:

receiving, with an electronic device, content for an application object accessible to the electronic device;

associating a metadata tag for a topic to the content;

storing the association between the content and the metadata tag in an on-device local search index of the electronic device, wherein the content in the on-device local search index remains local to the electronic device and the on-device local search index is not exposed to an external server;

receiving a query search request and performing a query search for the query search request using the local search index to obtain a set of search results that includes the content;

determining a preference of a user for the topic based on a history of on-device interactions with the topic; and

causing a presentation of a category for at least some of the set of search results using at least the metadata tag of the content.

2. The non-transitory machine-readable medium of claim 1 , wherein determining a preference of the user for the topic comprises:

classifying one or more interactions by the user with search results on the topic.

3. The non-transitory machine-readable medium of claim 1 , wherein the method further comprises:

ranking search results for the category based on the history of on-device interactions with search results.

4. The non-transitory machine-readable medium of claim 1 , wherein the application object is from an application locally installed on the electronic device.

5. The non-transitory machine-readable medium of claim 1 , wherein the method further comprises:

performing an analysis on the application object, wherein the analysis is selected from the group consisting of latent semantic analysis, explicit semantic analysis, latent Dirichlet allocation, hierarchical Dirichlet process, non-negative matrix factorization, and expectation maximization;

extracting at least one topic from the analysis; and

adding the at least one topic to the metadata tag for the application object.

6. The non-transitory machine-readable medium of claim 1 , wherein the method further comprises:

retrieving an application category for the application; and

adding the application category to the metadata tag as a topic for the application object.

7. The non-transitory machine-readable medium of claim 1 , wherein the content is metadata relating to objects used with the application.

8. A method to index donated content from an application on a device, the method comprising:

receiving, with an electronic device, content for an application object accessible to the electronic device;

associating a metadata tag for a topic to the content;

storing the association between the content and the metadata tag in an on-device local search index of the electronic device, wherein the content in the on-device local search index remains local to the electronic device and the on-device local search index is not exposed to an external server;

receiving a query search request and performing a query search for the query search request using the local search index to obtain a set of search results that includes the content;

determining a preference of a user for the topic based on a history of on-device interactions with the topic; and

causing a presentation of a category for at least some of the set of search results using at least the metadata tag of the content.

9. The method of claim 8 , wherein determining a preference of the user for the topic comprises:

classifying one or more interactions by the user with search results on the topic.

10. The method of claim 8 , wherein the method further comprises:

ranking search results for the category based on the history of on-device interactions with search results.

11. The method of claim 8 , wherein the application object is from an application locally installed on the electronic device.

12. The method of claim 8 , wherein the method further comprises:

performing an analysis on the application object, wherein the analysis is selected from the group consisting of latent semantic analysis, explicit semantic analysis, latent Dirichlet allocation, hierarchical Dirichlet process, non-negative matrix factorization, and expectation maximization;

extracting at least one topic from the analysis; and

adding the at least one topic to the metadata tag for the application object.

13. The method of claim 8 , wherein the method further comprises:

retrieving an application category for the application; and

adding the application category to the metadata tag as a topic for the application object.

14. The method of claim 8 , wherein the content is metadata relating to objects used with the application.

15. A device to index donated content from an application on a device, the device comprising:

at least one processor;

memory coupled to the processor through a bus; and

a process executed from the memory by the processor that causes the processor to:

receive, with an electronic device, content for an application object accessible to the electronic device;

associate a metadata tag for a topic to the content;

store the association between the content and the metadata tag in an on-device local search index of the electronic device, wherein the content in the on-device local search index remains local to the electronic device and the on-device local search index is not exposed to an external server;

receive a query search request and performing a query search for the query search request using the local search index to obtain a set of search results that includes the content;

determine a preference of a user for the topic based on a history of on-device interactions with the topic; and

cause a presentation of a category for at least some of the set of search results using at least the metadata tag of the content.

16. The device of claim 15 , wherein determining a preference of the user for the topic comprises:

classifying one or more interactions by the user with search results on the topic.

17. The device of claim 15 , wherein the process further causes the processor to:

ranking search results for the category based on the history of on-device interactions with search results.

18. The device of claim 15 , wherein the application object is from an application locally installed on the electronic device.

19. The device of claim 15 , wherein the process further causes the processor to:

performing an analysis on the application object, wherein the analysis is selected from the group consisting of latent semantic analysis, explicit semantic analysis, latent Dirichlet allocation, hierarchical Dirichlet process, non-negative matrix factorization, and expectation maximization;

extracting at least one topic from the analysis; and

adding the at least one topic to the metadata tag for the application object.

20. The device of claim 15 , wherein the process further causes the processor to:

retrieving an application category for the application; and

adding the application category to the metadata tag as a topic for the application object.

Continuity (4)

References Cited (55)