Systems and Methods for Recommending Software Applications

• US 20120303477A1
• Filed: 05/27/2011
• Published: 11/29/2012
• Est. Priority Date: 05/27/2011
• Status: Active Grant

• Current Assignee: Avast Software SRO (Gen Digital Inc.)
• Original Assignee: AVG Netherlands B.V. (Gen Digital Inc.)
• Inventors: Ben-Itzhak, Yuval
• Granted Patent: US 9,058,612 B2
• Time in Patent Office: Days
• US Class Current: 705/26.7
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A potentially beneficial software product is recommended to a user based, in part, on an analysis of parameters associated with the user'"'"'s usage of software applications already installed on the user'"'"'s computer.

Claims

1. A computer-implemented method for recommending a category of software applications, the method comprising:

programmatically collecting parameters associated with usage of one or more software applications installed on a computer;

mining the collected usage parameters to identify a potentially beneficial functionality not present on the computer; and

determining a category of software applications capable of performing the potentially beneficial functionality.

2. The method of claim 1, wherein one of the collected usage parameters comprises an execution parameter associated with the one or more installed software applications.

3. The method of claim 1, wherein one of the collected usage parameters comprises at least one of a system parameter and an application parameter.

4. The method of claim 3, wherein the system parameter comprises at least one of a processor type, size of available memory, disk-access time, and average data-reception time.

5. The method of claim 3, wherein the application parameter comprises at least one of a type of an installed software application, a number of files of a type, a size of a file, and a frequency of use of an installed application.

6. The method of claim 1, wherein the mining step comprises applying a rule to compare one of the collected usage parameters with a nominal value corresponding to that parameter.

7. The method of claim 1, wherein the mining step comprises statistically analyzing the collected usage parameters.

8. The method of claim 1, further comprising storing the collected usage parameters in a database.

9. The method of claim 8, wherein the database comprises one of a local database, a remote database, or a centralized database.

10. The method of claim 1, wherein the software-application category is one of back-up software, indexing software, database software, and system-maintenance software.

11. The method of claim 1, further comprising recommending a software application belonging to the determined category, the software application being cataloged in a software-application inventory database.

12. A computer-implemented method of recommending a software application, the method comprising:

programmatically collecting, at a computer, parameters associated with usage by a user of one or more software applications installed on the computer;

statistically analyzing the collected usage parameters based on reference parameters to (i) identify a potentially beneficial software application not present on the computer, and (ii) determine a likelihood of the user using the identified software application; and

recommending to the user the identified software application, based on the determined likelihood of the user using the identified software application.

13. The method of claim 12, further comprising at least one of installing and executing the identified software application on the computer.

14. The method of claim 12, further comprising storing the collected usage parameters in a database located at the computer.

15. The method of claim 12, further comprising generating the reference parameters by programmatically collecting parameters associated with usage of one or more software applications installed on one or more other computers.

16. The method of claim 12, further comprising generating the reference parameters by programmatically collecting parameters associated with usage by one or more other users of one or more software applications installed on the same computer.

17. The method of claim 12, wherein the analyzing step comprises clustering comprising determining a co-occurrence between two installed software applications based on at least one of the collected usage parameters and the reference parameters.

18. The method of claim 12, wherein one of the collected usage parameters comprises at least one of a type of the one or more installed software applications, a number of files of a type, size of a file, an association between a file type and the one or more installed software applications, frequency of use of each one of the one or more installed software applications, and average time of a single use of each one of the one or more installed software applications.

19. A system for recommending a category of software applications, the system comprising:

a profiler module for programmatically collecting parameters associated with usage of one or more software applications installed on a computer; and

a miner module for (i) mining the collected usage parameters to identify a potentially beneficial functionality not present on the computer, and (ii) determining a category of software applications capable of performing the identified functionality.

20. The system of claim 19, further comprising a database module for storing the collected usage parameters.

21. The system of claim 20, wherein the database module is configured to store at least one of (i) a rule applied by the miner to identify the potentially beneficial functionality, and (ii) a nominal value corresponding to one of the usage parameters.

22. The system of claim 20, wherein the profiler module, the miner module, and the database module are located at one computer.

23. The system of claim 20, wherein the profiler module is located at a first computer, and the miner module and the database module are located at a second computer.

24. The system of claim 19, further comprising an inventory module comprising an inventory database, for recommending a software application belonging to the determined category, the software application being cataloged in the inventory database.

25. A system for recommending a software application, the system comprising:

a profiler module for programmatically collecting parameters associated with usage by a user of one or more software applications installed on a computer;

a database module for storing the collected usage parameters; and

an analyzer module for statistically analyzing the collected usage parameters based on reference parameters to (i) identify a potentially beneficial software application, (ii) determine a likelihood of the user using the identified software application, and (iii) recommend to the user the identified software application, based on the likelihood of the user using the identified software application.

26. The system of claim 25, further comprising an installer for installing the identified software application on the computer.

27. The system of claim 25, further comprising a reference database module for storing the reference parameters.