User Model Data Exchange via Atomic Component Segmentation
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Solution Overview
Problem
Current user modeling systems in ubiquitous computing require users to bootstrap a new user model for each application or service, leading to inefficiencies due to proprietary models, lack of reusable components, and high development efforts for comprehensive information management.
Innovation Solution
The info-beads User Modeling approach, which defines atomic components that can be composed and reused to dynamically construct user models, allowing for the exchange and updating of user model data objects between devices and servers, enabling personalized services without manual bootstrapping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a complete user model is stored locally on each device, then service personalization is improved, but device storage requirements and data synchronization complexity increase
Solution Approach 1:
The user model is segmented into multiple data components, each representing a specific user attribute or information element. These components can be independently managed, stored, and synchronized between devices and servers, reducing the complexity of synchronizing entire user models while maintaining personalization capabilities.
Solution Approach 2:
The server is designed to perform multiple functions: storing user model data components, identifying missing components, providing missing components to clients, and enabling service personalization. This multi-functional server reduces the need for complex client-side synchronization logic.
2Loss of information
If user model data is exchanged between devices and servers, then user information availability is improved, but network communication overhead increases
Solution Approach 1:
The server proactively identifies missing data components in the user model and provides them to the client device before they are needed for service personalization. This preliminary action reduces the need for repeated communication cycles and minimizes network overhead.
Solution Approach 2:
The client device sends information about the identity of data components comprising its user model to the server. The server uses this feedback to identify missing components and respond accordingly, creating an efficient feedback loop that minimizes unnecessary data transmission.
3Adaptability or versatility
If atomic user model components are used for dynamic construction, then model flexibility and reusability are improved, but data component management complexity increases
Solution Approach 1:
The user model is divided into atomic data components that can be independently managed, exchanged, and composed. Each component represents a discrete user attribute, making the overall model more flexible and reusable across different services and devices while simplifying management through modular organization.
Solution Approach 2:
The server acts as an intermediary that manages the exchange and composition of atomic user model data components between devices. It handles the complexity of component identification, missing component provision, and model construction, freeing client devices from direct management complexity.
4Measurement precision
If manual user model bootstrapping is required for each application, then data accuracy is improved, but user time and development effort increase
Solution Approach 1:
The system performs preliminary actions by automatically identifying and providing missing user model data components from the server to the client device. This eliminates the need for manual bootstrapping while maintaining data accuracy, as the server supplies pre-validated components.
Solution Approach 2:
The client device automatically receives and integrates missing user model data components from the server without requiring manual user intervention. The system serves itself by autonomously completing the user model construction process, reducing both user time and development effort.
Data Source
AI summary
A method comprising: automatically providing, by a client device to a server, information regarding the identity of data components comprising a user model stored at the client device, wherein each of said data components is associated with an attribute of a user of the client device; automatically identifying, by said server, data components that are missing in said user model, based, at least in part, on a reference model stored at said server; automatically sending, by said server, to said client device, said identified missing data components; automatically updating, by said client device, said user model to include said identified missing data components; and automatically sending, by said client device, data contained in one or more of said data components in said updated user model, to enable a service provided by said server.