Token-Based Information Exchange for Privacy-Preserving Recommendations
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Solution Overview
Problem
Existing recommendation systems face challenges in exchanging user preferences between entities, as user preferences are often unknown or incommensurate across domains, and collecting history data threatens individual privacy, especially in ubiquitous computing environments where context-based recommendations are essential.
Innovation Solution
A method and system for exchanging information between computing units that detect events within a service, modify tokens associated with entities based on received information, and utilize these modified tokens to determine similarity measures for providing personalized services while maintaining user privacy through anonymous token interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If user preferences and history data are collected and exchanged between entities, then recommendation quality and service personalization are improved, but user privacy is compromised
Solution Approach 1:
The patent introduces tokens as intermediary data structures that mediate between user preferences and recommendation services. Instead of directly exchanging raw user data, entities exchange tokens that encapsulate preference information in a privacy-preserving manner. The token acts as a mediator that allows recommendation quality to improve while protecting user privacy by preventing direct access to sensitive user data.
Solution Approach 2:
The patent creates token copies that represent user preferences without copying the actual sensitive user data. These token copies can be exchanged and processed across multiple entities, enabling recommendation services to function with preference information while the original sensitive data remains protected and inaccessible to external entities.
2Adaptability or versatility
If tokens are modified and exchanged between multiple computing units, then service personalization and context-awareness are enhanced, but information exchange complexity increases
Solution Approach 1:
The patent segments the complex information exchange process into distinct operational phases: token creation, token modification, token exchange, and token utilization. Each computing unit performs specific segmented operations on tokens rather than managing entire data exchange workflows, which reduces individual device complexity while enabling sophisticated service personalization through coordinated token modifications across multiple entities.
3Measurement precision
If context information is collected for mobile computing units, then recommendation relevance is improved, but data collection requirements and system resources increase
Solution Approach 1:
The patent extracts only the essential preference information needed for recommendations into compact token structures, leaving out unnecessary detailed context data. This extraction approach allows the system to maintain high recommendation relevance by preserving key preference patterns while reducing data collection requirements and system resource consumption by not storing or processing unnecessary contextual details.
Data Source
AI summary
The invention relates to a method for exchange of information between a computing unit of a first entity and a computing unit of at least one second entity. A computing unit of at least one second entity is detected and information on a token associated to the second entity from the computing unit is requested and received. On the basis of the received information, the token associated to the at least one second entity, is retrieved and a token associated to the first entity is modified at least partly with information of the received token associated to the at least one second entity. Finally, the modified token is utilized at least in the service the computing unit of the first entity belongs to. The invention relates also to a system and a computing unit implementing the method.