Gender Recognition via Usage Pattern Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current mobile technologies lack an effective method for accurately determining the gender of a user based on their usage patterns, which is essential for personalized services and applications.
Innovation Solution
A method involving a server that receives user characteristic data from a mobile terminal, matches it with predetermined user characteristic data samples, queries a correspondence between these samples and reference genders, and determines the user's gender, which is then sent back to the terminal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If user characteristic data is collected and analyzed to determine gender, then gender recognition accuracy is improved, but user privacy and data security concerns increase
Solution Approach 1:
The patent extracts only the necessary characteristic data elements (usage patterns, app preferences, browsing behavior) required for gender recognition while excluding sensitive personal information. This selective extraction approach enables accurate gender determination without collecting unnecessary private data, thus resolving the contradiction between accuracy and privacy protection.
Solution Approach 2:
The patent introduces an intermediary processing layer that analyzes usage patterns and translates them into gender probability distributions without exposing raw user data. This intermediary mechanism allows accurate gender recognition while maintaining data security, as the actual user characteristic data remains protected and only processed results are utilized.
2Reliability
If multiple user characteristic data samples are matched and analyzed, then gender recognition reliability is improved, but processing time and computational complexity increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing and organizing user characteristic data into structured formats before actual gender recognition. Usage patterns are pre-categorized and stored in an optimized manner, allowing rapid matching and analysis during the recognition process. This preliminary preparation reduces the computational burden during real-time processing while maintaining high reliability through comprehensive data analysis.
3Measurement precision
If comprehensive usage pattern data is collected from mobile terminals, then recognition accuracy is improved, but data transmission and storage requirements increase
Solution Approach 1:
The patent extracts only the essential usage pattern features required for accurate gender recognition, such as app category preferences, browsing time patterns, and interaction frequencies. By selecting and transmitting only these critical features rather than complete raw data, the system achieves high recognition accuracy while minimizing data transmission volume and storage requirements.
Data Source
AI summary
A method for gender recognition of a user and related products are provided. The method includes the following. A sever receives user characteristic data from a mobile terminal, where the user characteristic data is indicative of usage of the mobile terminal by the user. At least one user characteristic data sample matching the user characteristic data is determined from a predetermined set of user characteristic data samples. At least one reference gender corresponding to the at least one user characteristic data sample is obtained by querying a preset correspondence between user characteristic data samples and reference genders. Gender of the user is determined according to the at least one reference gender and the gender determined is sent to the mobile terminal.