SYSTEMS AND METHODS FOR DETERMINING RELATIONSHIPS BETWEEN MOBILE APPLICATIONS AND ELECTRONIC DEVICE USERS

• US 20130132938A1
• Filed: 11/22/2011
• Published: 05/23/2013
• Est. Priority Date: 11/22/2011
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Agarwal, Vikas, Mukherjea, Sougata, Mittal, Sumit
• Granted Patent: US 9,137,651 B2
• Time in Patent Office: Days
• US Class Current: 717/173
• CPC Class Codes: G06F 8/60 Software deployment
• CPC Class Codes: G06F 9/44 Arrangements for executing specific programs
• CPC Class Codes: H04W 4/21 for social networking applications

Abstract

A system and method are provided for generating a mobile software program for prospective users. Telecommunications data is received from a telecommunications source. Snapshot data is generated that is related to one or more software programs downloaded to an electronic device. A relevance matrix is generated from the generated snapshot data and the telecommunications data to determine a first software program of the one or more software programs for a predetermined first consumer of the electronic device users or to determine a plurality of second consumers of the electronic device users for receiving data related to a second software program of the plurality of the one or more software programs.

Claims

1. A computer-implemented method, comprising:

receiving telecommunications data related to a plurality of electronic device users from a telecommunications source;

generating snapshot data related to one or more software programs downloaded to an electronic device; and

generating a relevance matrix from the generated snapshot data and the telecommunications data to at least one of determine a first software program of the one or more software programs for a predetermined first consumer of the electronic device users and determine a plurality of second consumers of the electronic device users for receiving data related to a second software program of the plurality of the one or more software programs.

2. The computer-implemented method of claim 1, further comprising determining a channel for outputting at least one of data related to the first software program and the data related to the second software program.

3. The computer-implemented method of claim 2, wherein the channel includes at least one of a voice channel, an SMS channel, and a web channel.

4. The computer-implemented method of claim 1, wherein the telecommunications data includes at least one of user location data, social network data, and telecommunications profile data.

5. The computer-implemented method of claim 1, further comprising generating the relevance matrix from at least one of application metadata, historical data, and consumer profile data.

6. The computer-implemented method of claim 5, wherein the relevance matrix includes an application relevance matrix.

7. The computer-implemented method of claim 6, wherein the application relevance matrix includes weights for various dimensions that influence purchase behavior.

8. The computer-implemented method of claim 7, wherein the dimensions include telecom dimensions and non-telecom dimensions.

9. The computer-implemented method of claim 8, wherein the method further comprises considering the relevance of each telecom and non-telecom dimension in the relevance matrix with respect to values for the dimensions in the one or more software programs.

10. The computer-implemented method of claim 5, wherein the relevance matrix includes a consumer relevance matrix.

11. The computer-implemented method of claim 10, wherein the consumer relevance matrix includes weights for various dimensions that influence purchase behavior based on the user'"'"'s dynamic profile.

12. The computer-implemented method of claim 11, wherein the dimensions include telecom dimensions and non-telecom dimensions.

13. The computer-implemented method of claim 12, wherein the method further comprises considering the relevance of each telecom and non-telecom dimension in the relevance matrix with respect to values for these dimensions in consumer data.

14. The computer-implemented method of claim 5, further comprising:

refining results of a consumer search based on the relevance matrices.

15. A computer-implemented method, comprising:

characterizing telecom data related to an electronic device user;

correlating the telecom data with application download data and application and consumer metadata;

determining whether the online applications are relevant to the user; and

determining one or more relevant channels for the user.

16. The computer-implemented method of claim 15, further comprising identifying presence regions of a user based on the user'"'"'s past locations and duration of stay in those locations.

17. An application relevance core system, comprising:

a telecommunications data repository that includes telecommunications data related to a plurality of electronic device users that is received from a telecommunications source and snapshot data related to one or more software programs downloaded to an electronic device; and

a relevance determination engine that generates a relevance matrix from the snapshot data and the telecommunications data to at least one of determine a first software program of the one or more software programs for a predetermined first consumer of the electronic device users and determine a plurality of second consumers of the electronic device users for receiving data related to a second software program of the plurality of the one or more software programs.

18. The relevance core system of claim 17, wherein the relevance determination engine comprises:

an application relevance matrix module that determines weights for various dimensions that influence purchase behavior; and

a consumer relevance matrix module that determines weights for various dimensions that influence purchase behavior based on the user'"'"'s dynamic profile.

19. The relevance core system of claim 17, wherein the relevance determination engine determines a relevance score from at least one of the weights for various dimensions that influence purchase behavior and weights for various dimensions that influence purchase behavior based on the user'"'"'s dynamic profile.

20. The relevance core system of claim 19, further comprising:

a channel determination engine that determines a channel for outputting data related to the first software program and the data related to the second software program.

21. A computer program product, comprising:

a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising;

computer readable program code configured to receive telecommunications data related to a plurality of electronic device users from a telecommunications source;

computer readable program code configured to generate snapshot data related to one or more software programs downloaded to an electronic device; and

computer readable program code configured to generate a relevance matrix from the generated snapshot data and the telecommunications data to at least one of determine a first software program of the one or more software programs for a predetermined first consumer of the electronic device users and determine a plurality of second consumers of the electronic device users for receiving data related to a second software program of the plurality of the one or more software programs.