IP Library Patent Application 15795946
Patent Application
App. No. 15/795,946

SYSTEM AND METHOD FOR DETERMINING USER HEALTH

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Quick Facts
Patent No.
US None
App. No.
15/795,946
Abstract

A method, a system, and an article are provided for determining how active users and groups of users are in an online game and, based thereon, generating recommendations for users to join one or more of the groups. The method can include, for example, generating a representation of a health of each of a plurality of users of a virtual environment, and aggregating the user health representations to generate an aggregated health representation for each group. Based on the aggregated health representations, a recommendation to a selected user of the virtual environment can be generated for joining a recommended group from the plurality of groups.

Claims (55)

1 . A method, comprising:

performing by one or more computer processors:

generating a representation of a health of each of a plurality of users of a virtual environment,

wherein each health representation is based on a plurality of metrics generated for a respective user from a history of interactions of the respective user with the virtual environment, and

wherein each user is associated with one of a plurality of groups of users within the virtual environment;

aggregating the health representations of the users of each group to generate an aggregated health representation for each group,

wherein the aggregated health representation provides an indication of how active the group is in the virtual environment;

generating, based on the aggregated health representations, a recommendation to a selected user of the virtual environment for joining a recommended group from the plurality of groups; and

adding the selected user to the recommended group.

2 . The method of claim 1 , wherein the health representation of each user provides an indication of how active the user is within the virtual environment.

3 . The method of claim 1 , wherein generating the health representation comprises:

providing the plurality of metrics to a predictive model comprising at least one of a trained classifier and a regression model.

4 . The method of claim 3 , wherein generating the health representations further comprises:

transforming output from the predictive model to achieve a rebalancing of the health representations.

5 . The method of claim 1 , wherein the plurality of metrics comprises at least one of user login activity, user chat activity, user purchasing activity, and any combination thereof.

6 . The method of claim 1 , wherein aggregating the health representations comprises:

determining at least one of an average, a median, a maximum, and a minimum of the health representations of the users of each group.

7 . The method of claim 1 , wherein generating the recommendation comprises:

determining that the recommended group comprises an aggregated health representation that exceeds the aggregated health representations of other groups within the plurality of groups.

8 . The method of claim 7 , wherein the recommended group comprises an aggregated health representation that is a maximum of the aggregated health representations for the plurality of groups.

9 . The method of claim 1 , wherein generating the recommendation comprises:

matching a language preference of the selected user with a language preference of the recommended group.

10 . The method of claim 1 , wherein generating the recommendation comprises:

determining that the recommended group can accommodate the selected user.

11 . A system, comprising:

one or more processors programmed to perform operations comprising:

generating a representation of a health of each of a plurality of users of a virtual environment,

wherein each health representation is based on a plurality of metrics generated for a respective user from a history of interactions of the respective user with the virtual environment, and

wherein each user is associated with one of a plurality of groups of users within the virtual environment;

aggregating the health representations of the users of each group to generate an aggregated health representation for each group,

wherein the aggregated health representation provides an indication of how active the group is in the virtual environment;

generating, based on the aggregated health representations, a recommendation to a selected user of the virtual environment for joining a recommended group from the plurality of groups; and

adding the selected user to the recommended group.

12 . The system of claim 11 , wherein the health representation of each user provides an indication of how active the user is within the virtual environment.

13 . The system of claim 11 , wherein generating the health representation comprises:

providing the plurality of metrics to a predictive model comprising at least one of a trained classifier and a regression model.

14 . The system of claim 13 , wherein generating the health representations further comprises:

transforming output from the predictive model to achieve a rebalancing of the health representations.

15 . The system of claim 11 , wherein the plurality of metrics comprises at least one of user login activity, user chat activity, user purchasing activity, and any combination thereof.

16 . The system of claim 11 , wherein aggregating the health representations comprises:

determining at least one of an average, a median, a maximum, and a minimum of the health representations of the users of each group.

17 . The system of claim 11 , wherein generating the recommendation comprises:

determining that the recommended group comprises an aggregated health representation that exceeds the aggregated health representations of other groups within the plurality of groups.

18 . The system of claim 17 , wherein the recommended group comprises an aggregated health representation that is a maximum of the aggregated health representations for the plurality of groups.

19 . The system of claim 11 , wherein generating the recommendation comprises:

matching a language preference of the selected user with a language preference of the recommended group.

20 . An article, comprising:

a non-transitory computer-readable medium comprising executable instructions, the executable instructions being executable by one or more processors to perform operations comprising:

generating a representation of a health of each of a plurality of users of a virtual environment,

wherein each health representation is based on a plurality of metrics generated for a respective user from a history of interactions of the respective user with the virtual environment, and

wherein each user is associated with one of a plurality of groups of users within the virtual environment;

aggregating the health representations of the users of each group to generate an aggregated health representation for each group,

wherein the aggregated health representation provides an indication of how active the group is in the virtual environment;

generating, based on the aggregated health representations, a recommendation to a selected user of the virtual environment for joining a recommended group from the plurality of groups; and

adding the selected user to the recommended group.

Assignments (6)
RELEASE OF SECURITY INTEREST Recorded May 19, 2020
From: COMERICA BANK
To: MZ IP HOLDINGS, LLC
Reel/Frame 052706/0899 →
RELEASE OF SECURITY INTEREST Recorded May 19, 2020
From: MGG INVESTMENT GROUP LP, AS COLLATERAL AGENT
To: MACHINE ZONE, INC.; SATORI WORLDWIDE, LLC; COGNANT LLC
Reel/Frame 052706/0917 →
SECURITY INTEREST Recorded May 22, 2018
From: MZ IP HOLDINGS, LLC
To: COMERICA BANK
Reel/Frame 046215/0207 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 29, 2018
From: MACHINE ZONE, INC.
To: MZ IP HOLDINGS, LLC
Reel/Frame 045786/0179 →
NOTICE OF SECURITY INTEREST -- PATENTS Recorded Feb 2, 2018
From: MACHINE ZONE, INC.; SATORI WORLDWIDE, LLC; COGNANT LLC
To: MGG INVESTMENT GROUP LP, AS COLLATERAL AGENT
Reel/Frame 045237/0861 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 22, 2017
From: BOJJA, NIKHIL; FOX, MICHAEL; SPENCER, NATHAN; LAU, CALVIN; SEVERS, DAVID; KOIKE, ANDREW; GUO, SHIMAN
To: MACHINE ZONE, INC.
Reel/Frame 044472/0324 →