Age Estimation via Weighted Multi-Source Data Fusion
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Solution Overview
Problem
Existing methods for determining a user's age on the internet are inaccurate as they rely heavily on self-reported data and lack precise validation, leading to unreliable age estimation.
Innovation Solution
A system that utilizes multiple sources of age data from instant messaging tools and Social Networking Services (SNS), combining user-provided basic age data with reference age data from network questionnaires to calculate an accuracy ratio and configure initial weights, then uses these weights and age similarity scores to estimate the user's age, thereby increasing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If simple boundary value filtering is used to estimate user age, then the processing complexity is low, but the measurement precision is poor
Solution Approach 1:
The patent merges multiple data sources (user profile age, questionnaire age, social network age, messaging service age) into a unified age estimation system. By combining these diverse data sources with different weights, the system achieves higher measurement precision than any single source alone, resolving the contradiction between accuracy and complexity through data integration rather than complex processing of single sources.
Solution Approach 2:
The system changes the parameter of data reliability by introducing dynamic weight coefficients for different data sources. Instead of treating all age data equally, the system assigns different weights based on the credibility and accuracy of each source, allowing the estimation algorithm to adaptively prioritize more reliable data and improve overall measurement precision.
2Measurement precision
If multiple data sources with weight configuration are used, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The system performs preliminary action by pre-configuring weight coefficients for different data sources based on their inherent reliability. These weights are established beforehand through analysis of data quality characteristics, so that when age estimation is performed, the system can directly apply these pre-determined weights without complex real-time analysis, thereby improving precision while limiting the increase in processing complexity.
Solution Approach 2:
The system implements self-service by automatically collecting age data from multiple sources (user profiles, questionnaires, social networks, messaging services) without requiring manual intervention. The automated data collection and weight-based aggregation process reduces the need for complex manual verification and processing, allowing the system to manage multiple data sources efficiently.
3Reliability
If user-provided age data is used directly, then the ease of operation is high, but the reliability is poor
Solution Approach 1:
The system introduces an intermediary mechanism (weight-based aggregation algorithm) that mediates between user-provided age data and the final age estimation. Instead of directly accepting user input, the system processes it through multiple data sources and applies weighted combination, thereby improving reliability while maintaining ease of operation through automated processing.
Solution Approach 2:
The system achieves universality by using a multi-functional data collection approach that gathers age information from various sources (profiles, questionnaires, social networks, messaging services) through a unified process. This multi-functional approach improves reliability by cross-validating data while maintaining ease of operation through automated multi-source collection.
Data Source
AI summary
An initial weight is configured for each kind of basic age data, an age weight of the user in different basic age data is obtained according to the initial weight and age similarity of the user in different kinds of basic age data, and the age with the largest age weight is determined as the age of the user.