User Personality Prediction via Behavioral Data Analysis
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Solution Overview
Problem
Existing methods for providing customized services, such as content-based filtering and collaborative filtering, face challenges when dealing with large amounts of content, sequential consumption, or limited content, and traditional personality tests are expensive and time-consuming.
Innovation Solution
A method and apparatus for predicting and analyzing user personality using data from various devices in real and virtual worlds, employing a machine learning model pre-trained on user data to infer personality without requiring users to complete lengthy questionnaires.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional personality tests are used to provide customized services, then measurement precision of user personality is improved, but loss of time increases significantly
Solution Approach 1:
The patent creates a virtual copy of the personality test process by training a machine learning model on personality test data. The trained model then predicts personality traits from behavioral data without requiring users to complete actual personality tests, thus copying the measurement function while eliminating time consumption.
Solution Approach 2:
The patent performs preliminary action by pre-training the machine learning model on personality test data before actual use. The model learns personality patterns in advance from training datasets containing personality test results and behavioral correlations, enabling fast prediction without requiring users to undergo lengthy tests.
2Loss of time
If machine learning model is used to predict personality from behavioral data, then loss of time is reduced, but measurement precision may deteriorate
Solution Approach 1:
The machine learning model undergoes extensive pre-training on labeled personality data and behavioral data pairs. This preliminary training phase allows the model to learn complex mappings between behaviors and personality traits, ensuring high prediction accuracy when deployed for actual personality assessment.
Solution Approach 2:
The system incorporates feedback mechanisms where prediction results can be refined based on additional behavioral data or user confirmation. The model continuously improves by learning from prediction outcomes and adjusting its parameters to enhance measurement precision over time.
Data Source
AI summary
Proposed is a method of predicting and analyzing a user's personality. The method is performed by a user personality prediction system, and includes obtaining data related to the user from a nearby device of the user, the data related to the user being collected and obtained for a particular period of time set by the user, predicting the user's personality using a machine learning model pre-trained on the basis of the data related to the user, and analyzing the predicted personality of the user to obtain analysis data.