RECOMMENDING NATIVE APPLICATIONS

• US 20140052683A1
• Filed: 08/17/2012
• Published: 02/20/2014
• Est. Priority Date: 08/17/2012
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Kirkham, Stephen, Bilinski, Brandon
• Granted Patent: US 9,280,789 B2
• Time in Patent Office: Days
• US Class Current: 706/46
• CPC Class Codes: G06F 16/9562 Bookmark management
• CPC Class Codes: G06F 8/61 Installation
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: H04L 67/34 involving the movement of software or configuration parameters network booting or remote initial program loading [RIPL] G06F9/4416

Abstract

In one implementation, a computer-implemented method includes accessing, by a computer system, information that describes use of one or more computer-based services by a particular user from one or more computing devices that are associated with the particular user; identifying one or more native applications that are associated with the one or more services, wherein the one or more native applications are configured to be installed and executed by one or more types of mobile computing devices; determining whether to recommend the one or more native applications based on the information and one or more threshold levels of use of the one or more computer-based services; and providing, based on the determining, a recommendation that is associated with the particular user and that identifies at least one of the one or more native applications.

Claims

1. A computer-implemented method comprising:

accessing, by a computer system, information that describes use of one or more computer-based services by a particular user from one or more computing devices that are associated with the particular user;

identifying, by the computer system, one or more native applications that are associated with the one or more services, wherein the one or more native applications are configured to be installed and executed by one or more types of mobile computing devices;

determining, by the computer system, whether to recommend the one or more native applications based on the information and one or more threshold levels of use of the one or more computer-based services; and

providing, by the computer system based on the determining, a recommendation that is associated with the particular user and that identifies at least one of the one or more native applications for installation on a particular mobile computing device that is associated with the particular user.

2. The computer-implemented method of claim 1, wherein the information includes information that identifies one or more web browser bookmarks on the one or more computing devices.

3. The computer-implemented method of claim 1, wherein the information includes information that indicates a web browsing history for the particular user on the one or more computing devices.

4. The computer-implemented method of claim 1, wherein the information includes information that identifies email messages that were received or sent using the one or more computing devices.

5. The computer-implemented method of claim 1, wherein the information includes information that identifies one or more geographic locations of the one or more computing devices.

6. The computer-implemented method of claim 1, wherein the information is accessed for each of the one or more computing devices based on each of the one or more computing devices being either a desktop computing device or a laptop computing device.

7. The computer-implemented method of claim 6, further comprising:

comparing, using the information, i) first use of a particular computer-based service from the one or more computer-based services by the particular user on the one or more computing devices with ii) second use of the particular computer-based service by the particular user on the particular mobile computing device or other mobile computing devices;

wherein, when the first use is determined to exceed the second use by at least a threshold amount, a particular native application from the one or more native applications that corresponds to the particular computer-based service is determined to be recommended for installation on the particular mobile computing device.

8. The computer-implemented method of claim 1, wherein the one or more computing devices does not include the particular mobile computing device.

9. The computer-implemented method of claim 1, wherein the one or more threshold levels of use include a threshold frequency that the one or more computer-based services were accessed from the one or more computing devices over a period of time.

10. The computer-implemented method of claim 1, wherein the one or more threshold levels of use include a threshold duration of time that the one or more computer-based services were used over a period of time.

11. The computer-implemented method of claim 1, wherein the recommendation is provided to the particular mobile computing device.

12. The computer-implemented method of claim 11, wherein the recommendation causes the particular mobile computing device to automatically install the at least one of the one or more native applications.

13. The computer-implemented method of claim 11, wherein the recommendation causes the particular mobile computing device to provide a notification that identifies the at least one of the one or more native applications for installation on the particular mobile computing device.

14. The computer-implemented method of claim 1, wherein the recommendation is provided to another computer system that provides an application store service;

and

wherein the recommendation causes the at least one of the one or more native applications to be recommended to the particular user by the other computer system as part of the application store service.

15. A computer-implemented method comprising:

accessing, by a computer system, social network information that identifies a plurality of users who have at least a threshold acquaintance relationship on one or more social networks with a particular user;

identifying, by the computer system, one or more native applications that are i) installed on mobile computing devices that are associated with the plurality of users and ii) not installed on a particular mobile computing device that is associated with the particular user;

determining whether to recommend the one or more native applications based on a frequency of installation or use of the one or more native applications on the mobile computing devices that are associated with the plurality users; and

providing, by the computer system based on the determining, a recommendation that is associated with the particular user and that identifies at least one of the one or more native applications for installation on the particular mobile computing device.

16. The computer-implemented method of claim 15, wherein the frequency of installation or use corresponds to the one or more native applications being i) installed on at least a threshold number of the mobile computing devices that are associated with the plurality of users or ii) used by the mobile computing devices that are associated with the plurality of users at least a threshold number of times over a period of time.

17. The computer-implemented method of claim 15, further comprising determining strengths of relationships between the particular user and the plurality of users;

wherein the frequency of installation or use by each of the plurality of users is weighted based on the determined strengths of relationships to produce weighted frequency of installation or use; and

wherein the determination of whether to recommend the one or more native applications is performed using the weighted frequency of installation or use.

18. A computer system for providing recommendations for native mobile applications, the system comprising:

a data collection system that is programmed to access information that describes use of one or more computer-based services by a particular user from one or more computing devices that are associated with the particular user;

a native application discovery system that is programmed to identify one or more native applications that are associated with the one or more services, wherein the one or more native applications are configured to be installed and executed by one or more types of mobile computing devices;

a native application selection system that is programmed to determine whether to recommend the one or more native applications based on the information and one or more threshold levels of use of the one or more computer-based services; and

a recommendation unit that is programmed to provide, based on the determination by the native application selection system, a recommendation that is associated with the particular user and that identifies at least one of the one or more native applications for installation on a particular mobile computing device that is associated with the particular user.

19. The computer system of claim 18, wherein the information is accessed for each of the one or more computing devices based on each of the one or more computing devices being either a desktop computing device or a laptop computing device.

20. The computer system of claim 19, wherein the native application selection system is further programmed to:

compare, using the information, i) first use of a particular computer-based service from the one or more computer-based services by the particular user on the one or more computing devices with ii) second use of the particular computer-based service by the particular user on the particular mobile computing device or other mobile computing devices; and

select a particular native application from the one or more native applications for recommendation to the particular mobile computing device when the first use is determined to exceed the second use by at least a threshold amount.