Context-Aware UI Template Generation via Component Combination

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Solution Overview

Problem

Current user interface design methods are inefficient and time-consuming, as they do not adapt to real-time user context and cognitive state, leading to suboptimal user interface templates and prolonged development and deployment times.

Innovation Solution

A computer-implemented method that generates user interface templates by combining relevant components based on user and platform context, using machine learning to assess cognitive state and apply context-aware, validation, and business rules, thereby adapting the interface dynamically.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional user interface design methods are used, then developers can create functional user interfaces, but the design process is inefficient and time-consuming

Engineering Contradiction:

Improveuser interface design efficiencyVSAvoiddevelopment and deployment time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system pre-generates multiple user interface template options based on the action request and user context before the user needs to interact with the interface. By performing the template generation and selection process in advance, the system eliminates time-consuming manual design work during actual deployment, directly addressing the productivity-time loss contradiction.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system automatically generates and selects user interface templates without requiring manual developer intervention for each interface creation task. The automated template generation process uses machine learning to assess user context and cognitively state, then combines relevant components to create appropriate templates, significantly improving design efficiency while reducing deployment time.

Inventive Principle:

Principle #25Self-service

2Adaptability or versatility

If static user interface templates are used, then implementation is simple, but the interface cannot adapt to real-time user context and cognitive state

Engineering Contradiction:

Improveadaptation to user contextVSAvoidinterface generation complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system transitions from static templates to dynamic template generation by continuously assessing user context and cognitive state in real-time. The interface components and their arrangements are dynamically adjusted based on current user conditions, allowing the system to adapt to changing user needs while managing complexity through automated machine learning-based assessment and component combination.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes multiple parameters simultaneously including user context parameters, cognitive state parameters, and interface component parameters to generate optimized templates. By systematically varying and evaluating different parameter combinations using machine learning, the system achieves high adaptability to user context while the automated process manages the inherent complexity of coordinating these changes.

Inventive Principle:

Principle #35Parameter changes

3Manufacturing precision

If manual user interface component selection is used, then each component can be carefully chosen, but the process is time-consuming and does not leverage real-time context

Engineering Contradiction:

Improvecomponent selection accuracyVSAvoidtemplate generation speed

Core Design Contradiction:

Manufacturing precisionVSProductivity

Solution Approach 1:

The system uses machine learning to continuously assess user context and cognitive state, then feeds this information back into the template generation process to automatically select and combine appropriate interface components. This feedback loop ensures high component selection accuracy by basing decisions on real-time user data, while the automated nature of the process maintains high productivity without manual intervention.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system replaces manual mechanical component selection with an automated machine learning-based system. The machine learning model assesses user context and cognitively state, then automatically determines optimal component combinations, substituting the slow manual process with a fast automated one that maintains or improves selection accuracy through data-driven decisions.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS11544452B2Generating templates for automated user interface components and validation rules based on context

Publication Date: 2023.01.03 AIRBNB INC

AI summary

Generating a user interface template is provided. A user context corresponding to an action request by a user to perform a task on a computer is determined. A set of user interface templates corresponding to the action request by the user and the user context is retrieved. Components of different user interface templates within the set of user interface templates are compared. Relevant components of the different user interface templates are combined based on the action request by the user and the user context. The user interface template corresponding to the action request by the user and the user context is generated based on the combined relevant components of the different user interface templates.