Personal Profile Vector Generation for Privacy-Preserving Personalization
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Solution Overview
Problem
Existing personal profile construction technologies face challenges in preventing indiscriminate use of user information while enhancing personalization performance, and they are limited in providing personalized services across various domains due to restrictive data collection and usage concerns.
Innovation Solution
A method and apparatus for generating a personal profile that collects daily user data, extracts meaningful data, generates a user profile in single vector form using semantic information, and stores it for selective provision to services, incorporating data reproduction models to minimize error and ensure privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If user information is collected indiscriminately to enhance personalization performance, then personalization service quality improves, but privacy concerns and user data control rights are compromised
Solution Approach 1:
The patent segments user information processing into distinct functional modules: data collection, meaningful data extraction, semantic information analysis, and profile generation. This segmentation allows selective processing of only necessary data elements, preventing indiscriminate data collection while maintaining personalization effectiveness.
Solution Approach 2:
The patent introduces an intermediary processing layer between raw user data and personalization services. This intermediary extracts only meaningful data and generates semantic information, acting as a filter that prevents raw personal data from being directly used, thereby protecting privacy while enabling personalized services.
2Measurement precision
If comprehensive user data is collected across multiple services to improve personalization, then personalization accuracy enhances, but data security and user control over data usage deteriorate
Solution Approach 1:
The patent extracts only the essential meaningful data and semantic information from comprehensive user data, separating what is necessary for personalization from what is not. This extraction process reduces the data footprint to minimal necessary elements, improving security while maintaining personalization accuracy.
Solution Approach 2:
The patent transforms raw user data into a different parameter form - converting detailed personal information into aggregated semantic information and statistical patterns. This parameter transformation maintains the utility for personalization while reducing the sensitivity and security risks associated with raw data.
3Adaptability or versatility
If user data is stored and processed centrally to enable cross-service personalization, then service versatility improves, but system complexity and data management overhead increase
Solution Approach 1:
The patent creates a universal personal profile structure that can serve multiple services and applications. By generating a standardized semantic information representation, the system enables cross-service personalization without requiring separate data management systems for each service, reducing overall complexity.
Solution Approach 2:
The patent performs preliminary processing of user data to generate the personal profile in advance, before specific services are requested. This preliminary action consolidates data processing into a single upfront operation, avoiding the need for complex real-time data management across multiple services.
Data Source
AI summary
A method for generating a personal profile in a user device is provided. The user device extracts meaningful data from daily data of the user, extracts semantic information by analyzing the meaningful data, and then generates a current user profile having a single vector form using the meaningful data and the semantic information, and stores the current user profile in a data storage unit.