Online Game Behavior Correlation for Psychological Profile Personalization

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Solution Overview

Problem

Existing systems fail to accurately classify users in digital environments and adapt experiences based on their psychological attributes, leading to inefficiencies in engaging users long-term and maintaining accurate classifications over time.

Innovation Solution

A system that correlates user behavior patterns within online games with psychological attributes by assigning users to cohorts based on psychological profiles, using machine-readable instructions to determine correlations between user behavior patterns and psychological parameters, and adapts the online game experience accordingly.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If users are classified into cohorts based on psychological profiles using stated information, then user engagement and personalization are improved, but system complexity and data processing requirements increase

Engineering Contradiction:

Improveuser experience personalizationVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system segments users into distinct cohorts based on psychological profiles derived from stated information. This segmentation allows personalized experiences for different user groups while managing complexity through organized categorization rather than individualized processing for each user.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system changes psychological parameters into observable behavioral patterns that can be measured and correlated. By transforming abstract psychological attributes into quantifiable behavioral metrics, the system enables personalization without requiring direct measurement of complex psychological states.

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If user behavior patterns are correlated with psychological attributes over time, then classification accuracy is improved, but measurement and detection difficulty increase

Engineering Contradiction:

Improveclassification accuracyVSAvoidpsychological attribute measurement

Core Design Contradiction:

Measurement precisionVSDifficulty of detecting and measuring

Solution Approach 1:

The system uses behavioral patterns as an intermediary to measure psychological attributes. Instead of directly measuring complex psychological states, the system observes and correlates observable behaviors with psychological profiles, making measurement feasible through behavioral indicators.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system continuously collects behavioral data and correlates it with psychological profiles over time, creating a feedback loop that refines classification accuracy. This iterative process improves measurement precision by learning from accumulated behavioral observations.

Inventive Principle:

Principle #23Feedback

3Reliability

If existing systems wait for large samples of user behavior before classification, then classification reliability is improved, but user retention and engagement time are reduced

Engineering Contradiction:

Improveclassification reliabilityVSAvoiduser engagement time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary classification using stated information provided by users before extensive behavioral tracking is needed. This allows early personalization and engagement while the user is still actively exploring the system, rather than waiting for large behavioral samples to accumulate.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The classification system is dynamic and adaptive, evolving from initial stated information to refined behavioral correlations over time. The system adjusts its classification approach based on available data, transitioning from static user-provided information to dynamic behavioral pattern recognition as users engage more deeply.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS12377352B2Systems and methods to correlate user behavior patterns within an online game with psychological attributes of users

Publication Date: 2025.08.05 SOLSTEN INC

AI summary

Systems and methods to correlate user behavior patterns within an online game with psychological attributes of users exhibiting the user behavior patterns are disclosed. Exemplary implementations may: store user information associated with the individual users including assignments of the individual users to individual ones of different cohorts of users, wherein the different cohorts are associated with different psychological profiles, where a given psychological profile is defined by multiple psychological parameter values, and the users are assigned to the different cohorts based on the psychological parameter values; obtain performance information that characterizes performances of user behavior patterns by the individual users; and determine correlations between individual ones of the performances of the user behavior patterns and individual ones of the psychological parameters based on the obtained user behavior patterns, the assignments of the users to the cohorts, and commonalities in the psychological profiles of the users within the individual cohorts.