APPLICATION RECOMMENDATION DEVICES AND APPLICATION RECOMMENDATION METHOD

• US 20180012238A1
• Filed: 02/10/2015
• Published: 01/11/2018
• Est. Priority Date: 02/10/2015
• Status: Abandoned Application

• Current Assignee: Razer (Asia-Pacific) Pte. Ltd. (Razer Incorporated)
• Original Assignee: Razer (Asia-Pacific) Pte. Ltd. (Razer Incorporated)
• Inventors: Giannuzzi, Joseph Mario, Recinos, Jesse Michael
• Application Number:
  US15/548,934
• Publication Number:
  US 20180012238A1
• Time in Patent Office: Days
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0203 Market surveys; Market polls
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

According to various embodiments, an application recommendation device may be provided. The application recommendation device may include: a metrics determination circuit configured to determine a plurality of metrics; and a user input circuit configured to receive user input; a weight determination circuit configured to determine a plurality of weights based on the user input; a weighting circuit configured to determine a weighted metric based on weighting the plurality of metrics based on the plurality of weights; and a recommendation determination circuit configured to determine a recommended application based on the weighted metric.

Claims

1. An application recommendation device comprising:

a metrics determination circuit configured to determine a plurality of metrics; and

a user input circuit configured to receive user input;

a weight determination circuit configured to determine a plurality of weights based on the user input;

a weighting circuit configured to determine a weighted metric based on weighting the plurality of metrics based on the plurality of weights; and

a recommendation determination circuit configured to determine a recommended application based on the weighted metric.

2. The application recommendation device of claim 1,

wherein the plurality of metrics are pairwise different, and wherein each metric of the plurality of metrics comprises information indicating at least one of the following information:

applications used by a user of the application recommendation device;

gaming interests of the user;

application genres used by the user;

gaming genres used by the user;

trends of applications used by the user;

trends of games used by the user;

a profile of the user in social media;

recommendations of a friend of the user;

recommendations of a friend of a friend of the user;

events scheduled by the user;

time the user has used an application;

time the user has used a game;

presents of the user;

updated performed by the user;

patches performed by the user;

user-defined data.

3. The application recommendation device of claim 1,

wherein the metrics determination circuit is configured to determine at least a subset of the plurality of metrics from social media.

4. The application recommendation device of claim 1,

wherein the metrics determination circuit is configured to determine at least a subset of the plurality of metrics from a computer of the user.

5. The application recommendation device of claim 1,

wherein the user input comprises an instruction to select a metric of the plurality of metrics and to decrease a weight related to the selected metric.

6. The application recommendation device of claim 1,

wherein the user input comprises an instruction to select a metric of the plurality of metrics and to increase a weight related to the selected metric.

7. The application recommendation device of claim 1,

wherein the user input comprises a pre-determined value, and an instruction to select a metric of the plurality of metrics and to set a weight related to the selected metric to the pre-determined value.

8. The application recommendation device of claim 1,

wherein each metric of the plurality of metrics is indicated by a number;

wherein the weighting circuit is configured to determine the weighted metric based on, for each metric of the plurality of metrics, a multiplication, the multiplication based on the number indicating the metrics an a weight of the plurality of weights related to the metric, and wherein the weighting circuit is configured to determine the weighted metric based on summing up the results of the multiplications.

9. The application recommendation device of claim 1,

wherein the user input comprises an instruction to modify the recommendation.

10. The application recommendation device of claim 1,

wherein the user input comprises an instruction to filter the recommendation.

11. An application recommendation method comprising:

determining a plurality of metrics;

receiving user input;

determining a plurality of weights based on the user input;

determining a weighted metric based on weighting the plurality of metrics based on the plurality of weights; and

determining a recommended application based on the weighted metric.

12. The application recommendation method of claim 11,

wherein the plurality of metrics are pairwise different, and wherein each metric of the plurality of metrics comprises information indicating at least one of the following information:

applications used by a user of the application recommendation method;

gaming interests of the user;

application genres used by the user;

gaming genres used by the user;

trends of applications used by the user;

trends of games used by the user;

a profile of the user in social media;

recommendations of a friend of the user;

recommendations of a friend of a friend of the user;

events scheduled by the user;

time the user has used an application;

time the user has used a game;

presents of the user;

updated performed by the user;

patches performed by the user;

user-defined data.

13. The application recommendation method of claim 11, further comprising:

determining at least a subset of the plurality of metrics from social media.

14. The application recommendation method of claim 11, further comprising:

determining at least a subset of the plurality of metrics from a computer of the user.

15. The application recommendation method of claim 11,

wherein the user input comprises an instruction to select a metric of the plurality of metrics and to decrease a weight related to the selected metric.

16. The application recommendation method of claim 11,

wherein the user input comprises an instruction to select a metric of the plurality of metrics and to increase a weight related to the selected metric.

17. The application recommendation method of claim 11,

wherein the user input comprises a pre-determined value, and an instruction to select a metric of the plurality of metrics and to set a weight related to the selected metric to the pre-determined value.

18. The application recommendation method of claim 11,

wherein each metric of the plurality of metrics is indicated by a number;

wherein the application recommendation method further comprises determining the weighted metric based on, for each metric of the plurality of metrics, a multiplication, the multiplication based on the number indicating the metrics an a weight of the plurality of weights related to the metric, and wherein the application recommendation method further comprises determining the weighted metric based on summing up the results of the multiplications.

19. The application recommendation method of claim 11,

wherein the user input comprises an instruction to modify the recommendation.

20. The application recommendation method of claim 11,

wherein the user input comprises an instruction to filter the recommendation.