Supplemental Content Presentation Mode Selection

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Solution Overview

Problem

Existing natural language processing systems struggle to effectively render and rank supplemental content, leading to suboptimal user experiences in terms of visual versus audible content presentation.

Innovation Solution

A system that uses machine learning models to process user input, query supplemental content providers, and determine the optimal presentation mode (visual, audible, or combined) for supplemental content based on user interaction history and device capabilities.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If supplemental content is provided through natural language processing systems, then user interaction capability is enhanced, but user experience quality deteriorates due to suboptimal content presentation and ranking

Engineering Contradiction:

Improveuser interaction capabilityVSAvoiduser experience quality

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The system dynamically changes presentation parameters (visual vs. audible mode, content ranking) based on analyzed user preferences and contextual factors, transforming static content delivery into adaptive parameter optimization to resolve the contradiction between interaction capability and experience quality

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system implements feedback loops by analyzing user interactions with supplemental content and using this information to refine future presentation decisions, thereby improving user experience quality while maintaining enhanced interaction capability

Inventive Principle:

Principle #23Feedback

2Device complexity

If supplemental content is presented without optimized ranking and presentation mode selection, then system complexity is reduced, but information delivery effectiveness deteriorates

Engineering Contradiction:

Improvesystem complexityVSAvoidinformation delivery effectiveness

Core Design Contradiction:

Device complexityVSLoss of information

Solution Approach 1:

The system performs preliminary analysis of user preferences and contextual factors before presenting supplemental content, pre-determining optimal presentation modes and ranking to enhance information delivery effectiveness without adding complex real-time processing

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system automatically analyzes user preferences and optimizes content presentation without requiring manual intervention, enabling self-service optimization that improves information delivery while maintaining simple system operation

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS12230278B1Output of visual supplemental content

Publication Date: 2025.02.18 AMAZON TECH INC

AI summary

Techniques for outputting supplemental content are described. A system may receive input data corresponding to a user input, and determine and present output data responsive to the user input. After causing the output data to be presented, the system may determine supplemental content is to be presented. Based on this, the system may determine first presentation data representing first supplemental content is to be visually presented, and second presentation data representing second supplemental content is to be audibly presented. The system may use a machine learning model to determine the first supplemental content is to be presented instead of the second supplemental content. The system may thereafter cause a device to use the first presentation data to visually present the first supplemental content.