Intelligent recommendations for gameplay session adjustment

Patent metadata

Field	Value
Publication number	US-11724198-B2
Application number	US-202117399773-A
Country	US
Kind code	B2
Filing date	Aug 11, 2021
Priority date	Aug 11, 2021
Publication date	Aug 15, 2023
Grant date	Aug 15, 2023

Abstract

Systems and methods for monitoring gameplay for monitoring real-time gameplay object data that is used to extract patterns in gameplay for generating notifications regarding control options based on extracted patterns. The notifications may indicate that selected conditions may be met based on the activity data that may be analyzed based on learning models associated with the selected conditions. The learning models may include models regarding player behavior, such as bullying or harassing language. The extract patterns may include gameplay session length, type of game played, and in-game behavior. Supervising accounts may receive recorded media segments associated with the activity data that met the selected conditions. And the user accounts engaging in such activities may be blocked and/or provided suggestions regarding alternative activities.

First claim

What is claimed is:

1. A method for developing and customizing learning models regarding gameplay, the method comprising:
storing information in memory regarding a user account and one or more selected conditions;
monitoring activity data from a plurality of gameplay sessions of a plurality of interactive content titles, the activity data associated with the user account;
analyzing the activity data to extract one or more gameplay patterns exhibited by the user account associated with the selected conditions, wherein analyzing the activity data is based on one or more learning models associated with the selected conditions, wherein at least one of the learning model is associated with the user account;
generating a notification that includes one or more gameplay control options based on the learning models associated with the extracted patterns indicating that one or more of the selected conditions are met by the activity data; and
refining the at least one learning model based on one or more selected gameplay control options and one or more outcomes of each gameplay control option.

2. The method of claim 1 , wherein the one or more learning models pertain to player behavior that includes bullying or harassing language.

3. The method of claim 1 , wherein the extracted gameplay patterns are associated with at least one of gameplay session length, type of game played, and in-game behavior.

4. The method of claim 1 , further comprising sending the notification to a user device associated with a supervisory user account, wherein the gameplay control options are selectable via a mobile application of the user device.

5. The method of claim 1 , wherein the gameplay control options include at least one of throttling game time, requiring activity diversification, or flagging in-game behaviors that meet the selected conditions.

6. The method of claim 1 , wherein the selected conditions include a schedule or calendar designated by a supervisory user account, and further comprising toggling between different gameplay control modes for the user account based on the designated schedule or calendar.

7. The method of claim 1 , further comprising:
recording media segments of gameplay by the user account based on one or more timestamps associated with the activity data that met the selected conditions; and
providing the recorded media segments to a supervisory user account.

8. The method of claim 7 , wherein the supervisory user account opts to implement a gameplay control option to require activity diversification, and further comprising:
blocking the user account from engaging in a current activity for a predetermined period of time; and
suggesting one or more alternative activities that are currently available to the user account.

9. The method of claim 1 , further comprising customizing the at least one learning model based on the extracted patterns.

10. A system for developing and customizing learning models regarding gameplay, the system comprising:
memory that stores information regarding a user account and one or more selected conditions;
a communication interface that receives activity data sent over a communication network from a plurality of gameplay sessions of a plurality of interactive content titles, the activity data associated with the user account; and
a processor that executes instructions stored in memory, wherein the processor executes the instructions to:
monitor the activity data;
analyze the activity data to extract one or more gameplay patterns exhibited by the user account associated with the selected conditions, wherein analyzing the activity data is based on one or more learning models associated with the selected conditions, wherein at least one of the learning model is associated with the user account;
generate a notification that includes one or more gameplay control options based on the learning models associated with the extracted patterns indicating that one or more of the selected conditions are met by the activity data; and
refine the at least one learning model based on one or more selected gameplay control options and one or more outcomes of each gameplay control option.

11. The system of claim 10 , wherein the one or more learning models pertain to player behavior that includes bullying or harassing language.

12. The system of claim 10 , wherein the extracted patterns are associated with at least one of gameplay session length, type of game played, and in-game behavior.

13. The system of claim 10 , wherein the communication interface further sends the notification over the communication network to a user device associated with a supervisory user account, wherein the gameplay control options are selectable via a mobile application of the user device.

14. The system of claim 10 , wherein the gameplay control options includes at least one of throttling game time, requiring activity diversification, or flagging in-game behaviors that meet the selected conditions.

15. The system of claim 10 , wherein the selected conditions include a schedule or calendar designated by a supervisory user account, and further comprising toggling between different gameplay control modes for the user account based on the designated schedule or calendar.

16. The system of claim 10 , wherein the processor executes further instructions to:
record media segments of gameplay by the user account based on one or more timestamps associated with the activity data that met the selected conditions; and
provide the recorded media segments to a supervisory user account.

17. The system of claim 16 , wherein the supervisory user account opts to implement a gameplay control option to require activity diversification, and wherein the processor executes further instructions to:
block the user account from engage in a current activity for a predetermined period of time; and
suggest one or more alternative activities that are currently available to the user account.

18. The system of claim 10 , wherein the processor executes further instructions to customize the at least one learning model based on the extracted patterns.

19. A non-transitory computer-readable medium comprising instructions, the instructions, when executed by a computing system, cause the computing system to:
storing information in memory regarding a user account and one or more selected conditions;
monitoring activity data from a plurality of gameplay sessions of a plurality of interactive content titles, the activity data associated with the user account;
analyzing the activity data to extract one or more gameplay patterns exhibited by the user account associated with the selected conditions, wherein analyzing the activity data is based on one or more learning models associated with the selected conditions, wherein at least one of the learning model is associated with the user account;
generating a notification that includes one or more gameplay control options based on the learning models associated with the extracted patterns indicating that one or more of the selected conditions are met by the activity data; and
refining the at least one learning model based on one or more selected gameplay control options and one or more outcomes of each gameplay control option.

Assignees

• Sony Interactive Entertainment LLC

Inventors

• Fortuna Ellana
• Thompson Erikka
• Juenger Elizabeth

Classifications

• A63F13/75 Primary

  Enforcing rules, e.g. detecting foul play or generating lists of cheating players · CPC title

• A63F13/71

  using secure communication between game devices and game servers, e.g. by encrypting game data or authenticating players · CPC title

• A63F13/79

  involving player-related data, e.g. identities, accounts, preferences or play histories · CPC title

• A63F13/85

  Providing additional services to players · CPC title

• A63F13/49 Primary

  Saving the game status; Pausing or ending the game · CPC title