Application recommendations based on application and lifestyle fingerprinting

• US 10,037,548 B2
• Filed: 02/12/2016
• Issued: 07/31/2018
• Est. Priority Date: 06/25/2013
• Status: Expired due to Fees

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Evans, Ethan Zane, Markley, David Allen, Adkins, III, James Newton
• Primary Examiner(s): NGUYEN, CAM LINH T
• Application Number:
  US15/042,281
• Publication Number:
  US 20160162942A1
• Time in Patent Office: 900 Days
• Field of Search: 707736, 707758, 707749, 707767
• CPC Class Codes: G06F 16/24 Querying
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/288 Entity relationship models
• CPC Class Codes: G06F 16/738 Presentation of query results
• CPC Class Codes: G06F 16/90324 using system suggestions
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0272 Period of advertisement exposure

Abstract

Disclosed are various embodiments that employ application fingerprinting and lifestyle fingerprinting, where each application fingerprint is associated with a corresponding application and is generated based at least in part on a static analysis and a dynamic analysis of the corresponding application. In one embodiment, an identification of an application is received, and a group of users are determined that have a preference for the application based at least in part on lifestyle fingerprint data and application fingerprint data. Correspondingly, a particular user is identified with a lifestyle fingerprint that is similar to lifestyle fingerprints of the group of users, whereby the particular application is transmitted to the particular user.

Claims

1. A method comprising:

maintaining, via at least one computing device, a plurality of application fingerprints in a data store, individual ones of the plurality of application fingerprints being associated with a corresponding one of a plurality of applications, the individual ones of the plurality of application fingerprints being generated based at least in part on a static analysis and a dynamic analysis of the corresponding one of the plurality of applications, wherein the dynamic analysis comprises an analysis of computing device resources consumed by the corresponding one of the plurality of applications;

maintaining, via the at least one computing device, a plurality of lifestyle fingerprints in the data store, individual ones of the plurality of lifestyle fingerprints being associated with a corresponding plurality of users;

receiving, via the at least one computing device, an identification of a particular application;

determining, via the at least one computing device, a group of users based at least in part on lifestyle fingerprint data for the group of users indicating a prior usage of the particular application;

identifying, via the at least one computing device, a particular user based at least in part on comparing a lifestyle fingerprint of the particular user with lifestyle fingerprints of the group of users and identifying a correlation between the lifestyle fingerprints of the particular user and the group of users that indicates a preference for one or more attributes associated with an application fingerprint of the particular application, wherein the lifestyle fingerprint of the particular user indicates that the particular user has not previously used the particular application; and

implementing, via the at least one computing device, a test trial of the particular application by electronically sending a copy of the particular application to the particular user responsive to identifying the particular user as having the preference for the one or more attributes associated with the application fingerprint of the particular application and responsive to identifying that the lifestyle fingerprint of the particular user indicates that the particular user has not previously used the particular application.

2. The method of claim 1, further comprising monitoring, via the at least one computing device, usage of the particular application by the particular user during a period of the test trial and updating the lifestyle fingerprint of the particular user based at least in part on usage information obtained from the test trial.

3. The method of claim 1, wherein the lifestyle fingerprint of the particular user indicates that the particular user has a preference for application test trials.

4. The method of claim 1, further comprising updating the application fingerprint of the particular application based at least in part on a behavioral analysis of usage of an instance of the particular application by the particular user.

5. The method of claim 4, wherein the behavioral analysis processes at least one of a location of the at least one client computing device during execution of the instance of the particular application, a duration of use for the instance of the particular application, or a time of day that the instance of the particular application is executed.

6. A system, comprising:

at least one computing device; and

at least one service executable in the at least one computing device, the at least one service configured to at least;

determine an application fingerprint for individual ones of a plurality of applications, the individual ones of the plurality of application fingerprints being based at least in part on a static analysis and a dynamic analysis of a corresponding one of the plurality of applications, wherein the dynamic analysis comprises an analysis of computing device resources consumed by the corresponding one of the plurality of applications;

determine a lifestyle fingerprint for individual ones of a plurality of users, a respective lifestyle fingerprint being indicative of at least one or more application preferences of a user and application usage information for the user;

determine a group of users based at least in part on lifestyle fingerprint data for the group of users indicating a prior usage of a particular application, wherein the plurality of applications comprises the particular application and the plurality of users comprises the group of users;

determine a particular user based at least in part on comparing a lifestyle fingerprint of the particular user with lifestyle fingerprints of the group of users and identifying a correlation between the lifestyle fingerprints of the particular user and the group of users that indicates a preference for one or more attributes associated with an application fingerprint of the particular application, wherein the lifestyle fingerprint of the particular user indicates that the particular user has not previously used the particular application, wherein the particular user is associated with a geographic region that is not shared with the group of users; and

electronically transmit, via the at least one computing device, a copy of the particular application to the particular user responsive to identifying the particular user as having the preference for the one or more attributes associated with the application fingerprint of the particular application and responsive to identifying the particular user as being associated with a geographic region that is not shared with the group of users.

7. The system of claim 6, wherein the lifestyle fingerprint is based at least in part on application usage data, application download data, purchase data, or a device profile.

8. The system of claim 6, wherein the application fingerprint indicates a set of code fragments employed by a respective application and a set of device resources employed by the respective application.

9. The system of claim 6, wherein the application fingerprint of the particular application indicates one or more code fragments indicative of code that matches one or more preferences of the user as indicated by the lifestyle fingerprint of the user.

10. The system of claim 6, wherein the at least one service is further configured to at least generate a recommendation of the particular application to the particular user.

11. The system of claim 6, wherein the at least one service is further configured to at least generate a pricing model recommendation for the particular application based at least in part on the lifestyle fingerprint of the particular user and the application fingerprint of the particular application.

12. The system of claim 6, wherein the at least one service is further configured to at least send data to a client computing device associated with the particular user, the data configured to include one or more of an upgrade to the particular application, an advertisement, or an in-application item.

13. The system of claim 6, wherein the lifestyle fingerprint of the user indicates a characteristic of initiating a purchase transaction during application use.

14. The system of claim 6, wherein the lifestyle fingerprint indicates that the user has a preference for free application trials.

15. The system of claim 6, wherein the dynamic analysis processes a resource consumption pattern of a client computing device during execution of an instance of the particular application.

16. The system of claim 6, wherein the at least one service is further configured to at least update the lifestyle fingerprint of the particular application based at least in part on a behavioral analysis of usage of an instance of the particular application by the particular user.

17. A method, comprising:

performing, by at least one computing device, an analysis of computing device resources consumed by a corresponding one of a plurality of applications;

generating, by the at least one computing device, a plurality of application fingerprints in a data store, individual ones of the plurality of application fingerprints being generated based at least in part on the analysis of computing device resources consumed by the corresponding one of the plurality of applications;

maintaining, by the at least one computing device, the plurality of application fingerprints in the data store, the individual ones of the plurality of application fingerprints being associated with corresponding ones of the plurality of applications;

receiving, by the at least one computing device, a selection of a first application, the plurality of applications comprising the first application and a second application;

determining, by the at least one computing device, that the second application is similar to the first application by comparing characteristics of a first application fingerprint for the first application with characteristics of a second application fingerprint of the second application;

identifying, by the at least one computing device, a first group of users who have at least used the first application based at least on a lifestyle fingerprint of individual ones of the first group of users, wherein the lifestyle fingerprint comprises usage information of a user;

identifying, by the at least one computing device, a second group of users who have at least used the second application based on the lifestyle fingerprint of individual ones of the second group of users;

determining, by the at least one computing device, a geographic region that is shared by the second group of users and is not shared by the first group of users;

identifying, by the at least one computing device, a particular user that has not previously used the first application and is associated with a the geographic region that is not shared with the first group of users, wherein a lifestyle fingerprint of the particular user further indicates a preference for the first application; and

sending, by the at least one computing device, an invitation to test the first application to a client computing device of the user responsive to identifying the particular user as having the preference for the first application and responsive to determining that the particular user is from the geographic region that is not shared by the first group of users.

18. The method of claim 17, further comprising updating the lifestyle fingerprint of the user based at least in part on a behavioral analysis of usage of an instance of the first application by the user.

19. The method of claim 18, wherein the behavioral analysis processes at least one of a location of the client computing device during execution of the instance of the first application, a duration of use for the instance of the first application, or a time of day that the instance of the first application is executed.

20. The method of claim 17, wherein the lifestyle fingerprint of the user indicates a preference for application test trials.