Recommendation Model Management for Multi-User Scenarios
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Solution Overview
Problem
Current recommendation frameworks fail to provide personalized user experiences for multi-user, multi-account, and multi-device scenarios, as they associate single user behavior with devices, neglecting the duality or multiplicity of user behavior and account usage.
Innovation Solution
A system that processes user identification characteristics and determines user identities and active communication accounts to associate personalized recommendation models with user identities, communication accounts, and devices, enabling tailored experiences across various user and account combinations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single user behavior model is associated with a device, then the recommendation framework is simple to implement, but it fails to provide personalized experiences for multi-user and multi-account scenarios
Solution Approach 1:
The patent segments the recommendation model management by introducing hierarchical identifiers: user identities, communication accounts, and devices. Each layer can be independently managed and associated with recommendation models, allowing personalized recommendations for different users/accounts on the same device while maintaining separate model associations for each segment.
Solution Approach 2:
The patent adds dimensional layers to the recommendation framework by introducing user identity and communication account dimensions alongside the device dimension. This multi-dimensional association structure enables the system to handle multi-user, multi-account scenarios without requiring complete redesign of the recommendation engine.
2Adaptability or versatility
If multiple recommendation models are associated with different user identities and accounts, then personalized user experiences are achieved, but the system complexity increases
Solution Approach 1:
The patent creates a universal association mechanism that works across multiple dimensions (user identities, communication accounts, devices). The same recommendation model can be associated with different combinations of these identifiers, allowing the system to serve multiple purposes: single-user recommendations, multi-user recommendations, account-specific recommendations, and device-level recommendations, all through a unified framework.
3Measurement precision
If user identification characteristics are processed to determine user identities, then accurate personalization is achieved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary actions by establishing and storing associations between user identities, communication accounts, devices, and recommendation models in advance. When a user accesses the system, the pre-established associations enable quick retrieval and application of appropriate recommendation models without requiring complex real-time analysis, thus reducing processing time while maintaining identification accuracy.
Data Source
AI summary
A platform for managing recommendation models is described. The platform processes and/or facilitates a processing of at least one user identification characteristic associated with at least one device to determine a user identity. The platform further determines at least one communication account active at the at least one device. The platform also causes, at least in part, an association of one or more recommendations models with the user identity, the at least one communication account, the at least one device, or a combination thereof.