Ranking of digital goods in a marketplace

• US 8,620,914 B1
• Filed: 05/18/2011
• Issued: 12/31/2013
• Est. Priority Date: 05/18/2010
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Noth, Michael, Chew, Chee Heng, Roy-Chowdhury, Rahul, Kay, Erik, Huang, Qian, Fang, Qinming
• Primary Examiner(s): Boccio, Vincent F
• Application Number:
  US13/110,907
• Time in Patent Office: 958 Days
• Field of Search: 703/22, 702/182, 702185-186, 707/736, 707/748, 707/751, 707/732
• US Class Current: 707/732
• CPC Class Codes: G06F 11/0766 Error or fault reporting or storing
• CPC Class Codes: G06F 16/95 Retrieval from the web
• CPC Class Codes: G06F 16/9566 URL specific, e.g. using aliases, detecting broken or misspelled links
• CPC Class Codes: G06F 16/9574 of access to content, e.g. by caching
• CPC Class Codes: G06F 16/9577 Optimising the visualization of content, e.g. distillation of HTML documents
• CPC Class Codes: G06F 16/958 Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
• CPC Class Codes: G06F 21/53 by executing in a restricted environment, e.g. sandbox or secure virtual machine
• CPC Class Codes: G06F 21/57 Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 8/61 Installation
• CPC Class Codes: G06F 9/44526 Plug-ins; Add-ons
• CPC Class Codes: G06F 9/54 Interprogram communication
• CPC Class Codes: G06Q 30/0609 Buyer or seller confidence or verification
• CPC Class Codes: H04L 51/212 using filtering or selective blocking
• CPC Class Codes: H04L 63/0823 using certificates cryptographic mechanisms or cryptographic arrangements for entity authentication involving certificates H04L9/3263
• CPC Class Codes: H04L 63/1483 service impersonation, e.g. phishing, pharming or web spoofing detection of rogue wireless access points H04W12/12
• CPC Class Codes: H04L 67/01 Protocols
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/289 Intermediate processing functionally located close to the data consumer application, e.g. in same machine, in same home or in same sub-network
• CPC Class Codes: H04L 67/34 : involving the movement of software or configuration parameters network booting or remote initial program loading [RIPL] G06F9/4416
• CPC Class Codes: H04L 67/564 : Enhancement of application control based on intercepted application data
• CPC Class Codes: H04L 67/568 : Storing data temporarily at an intermediate stage, e.g. caching

Abstract

According to one general aspect, a method of presenting to a user a subset of applications that may be executed by a computing device is described. The subset of applications may be selected from a plurality of applications available an online marketplace for such applications. The method may include ranking the applications based on signals relevant to the relative desirability to the user of different applications, wherein at least one of the signals is based on information that is generated outside of the marketplace. The method may further include selecting the subset of applications based on their respective rankings. The method may also include presenting the selected subset to the user.

Claims

1. A method of presenting to a user a subset of applications that are installable for use in a web browser executed by a computing device, the subset of applications being selected from a plurality of applications available in an online marketplace for such applications, the method comprising:

ranking the applications based on signals relevant to the relative desirability to the user of different applications, wherein at least one of the signals is based on information that is generated outside of the marketplace, wherein at least one of the signals is based on information about how applications available from the marketplace are used by client computing devices or about how the applications perform when utilized by a client computing device, wherein such information is generated automatically when the applications are executed by a web browser running on a client computing device;

selecting the subset of applications based on their respective rankings; and

presenting the selected subset to the user.

2. The method of claim 1, wherein at least one of the signals based on how the applications perform when utilized by a client computing device includes a signal that is based on a rate at which an application crashes while being executed by a computing device.

3. The method of claim 2, wherein the signal based on the rate at which the application crashes while executing is determined based on information about that crash rate that is received from browsers that execute the application.

4. The method of claim 1, wherein at least one of the signals based on how the applications perform when utilized by a client computing device includes a signal that is based on a response time of an application while being executed by a computing device.

5. The method of claim 1, wherein at least one of the signals based on information that is generated outside the marketplace includes a signal that is based on how often an application is used after it is downloaded from the marketplace.

6. The method of claim 5, further comprising:

receiving information from a plurality of client devices about how often the application is front-facing within a user interface of the client device for executing the application; and

generating the signal that is based on how often an application is used after it is downloaded from the marketplace based on the received information.

7. The method of claim 5, further comprising:

receiving information from a plurality of client devices about how often the application is launched within a user interface of the client device for executing the application; and

generating the signal that is based on how often an application is used after it is downloaded from the marketplace based on the received information.

8. The method of claim 5, further comprising:

receiving information from a plurality of client devices about how often the application is open within a user interface of the client device for executing the application; and

generating the signal that is based on how often an application is used after it is downloaded from the marketplace on the received information.

9. The method of claim 1, wherein at least one of the signals based on information that is generated outside the marketplace includes a signal that is based on recent trends in query terms, related searches, and results received through a search engine.

10. The method of claim 1, wherein at least one of the signals based on information that is generated outside the marketplace includes a signal that is based on how often an application is recommended by a user of the application to acquaintances in social networks of the user.

11. The method of claim 1, wherein the ranking of the applications is specific to a user, and wherein at least one of the signals based on information that is generated outside the marketplace includes a signal that is based on how often an application is used by acquaintances in social networks of the user.

12. The method of claim 1, wherein the ranking of the applications is specific to a user, and wherein at least one of the signals based on information that is generated outside the marketplace includes a signal that is based on how often an application is used by acquaintances in social networks of the user.

13. The method of claim 1, wherein the ranking of the applications is specific to a user, and wherein the method further comprises:

associating metadata with applications of the plurality of applications;

comparing the metadata associated with applications with information associated with the user; and

ranking the applications based on the comparisons.

14. The method of claim 13, wherein the information associated with the user includes information generated by the user.

15. The method of claim 14, wherein the information generated by the user includes:

information actively provided by a user, and

information inferred from user actions.

16. The method of claim 13, wherein the information associated with the user includes a browsing history of the user.

17. The method of claim 13, wherein the information associated with the user includes a location of the user.

18. A non-transitory, tangible computer-readable storage medium having recorded and stored thereon instructions that, when executed by one or more processors of a computer system cause the computer system to:

rank applications in a plurality of applications available in an online marketplace for applications that may be executed by a computing device based on signals relevant to the relative desirability to the user of different applications, wherein at least one of the signals is based on information that is generated outside of the marketplace;

select the subset of applications based on their respective rankings; and

present the selected subset to the user.

19. A system comprising:

one or more memory devices arranged and configured to store executable code; and

one or more processors operably coupled to the one or more memory devices, the processors being arranged and configured to execute the code such that the apparatus performs the actions of;

ranking applications in a plurality of applications available in an online marketplace for applications that may be installed for use in a web browser executed by a computing device, wherein the ranking is based on signals relevant to the relative desirability to a user of different applications, wherein at least one of the signals is based on information that is generated outside of the marketplace, wherein at least one of the signals is based on information about how applications available from the marketplace are used by client computing devices or about how the applications perform when utilized by a client computing device, wherein such information is generated automatically when the applications are executed by a web browser running on a client computing device;

selecting the subset of applications based on their respective rankings; and

presenting the selected subset to the user.