Content Agent for Dialog-Based Content Filtering

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Solution Overview

Problem

Existing human-to-computer dialog systems face inefficiencies in content rendering, as they often process large corpora of content without sufficient filtering, leading to increased computational overhead and user interaction friction.

Innovation Solution

A content agent is generated using content parameters determined from user requests and refined during dialog sessions, selectively constraining the corpus of content to reduce processing complexity and improve resource management, while allowing for proactive content rendering based on user preferences and context.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If a large corpus of content is processed without sufficient filtering, then content completeness is improved, but computational overhead increases

Engineering Contradiction:

Improvecontent quantityVSAvoidcomputational overhead

Core Design Contradiction:

Quantity of substanceVSDevice complexity

Solution Approach 1:

The system performs preliminary actions by generating prompts before content rendering to constrain and filter the corpus of content. These prompts are created based on user requests and dialog session context, allowing the system to pre-determine which content should be considered, thereby reducing computational overhead during actual content processing while maintaining relevance and completeness.

Inventive Principle:

Principle #10Preliminary action

2Manufacturing precision

If content parameters are refined during dialog sessions, then content relevance is improved, but interaction time increases

Engineering Contradiction:

Improvecontent relevanceVSAvoidinteraction time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The system implements feedback mechanisms where prompts generated during dialog sessions refine content parameters based on user responses. This iterative feedback loop allows the system to progressively narrow down content parameters, improving relevance while managing interaction time through efficient prompt-based filtering that reduces the need for extensive browsing.

Inventive Principle:

Principle #23Feedback

3Productivity

If selective dialog sessions are initiated to constrain content, then computational efficiency is improved, but resource requirements increase

Engineering Contradiction:

Improvecomputational efficiencyVSAvoidresource requirements

Core Design Contradiction:

ProductivityVSUse of energy by moving object

Solution Approach 1:

The system applies partial action by selectively initiating dialog sessions only when necessary to constrain content, rather than continuously engaging in refinement conversations. Prompts are generated and dialog sessions are triggered based on specific conditions, allowing the system to achieve computational efficiency through selective content constraint while managing resource requirements through conditional engagement.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS20240428004A1Rendering content using a content agent and/or stored content parameter(s)

Publication Date: 2024.12.26 GOOGLE LLC

AI summary

Techniques are disclosed that enable the generation of a content agent based on content parameter(s) determined from an initial user request for content as well as a dialog session to further refine the request for content. Various implementations include using the content agent to render additional content responsive to an additional user request. Additional or alternatively implementations include using the content agent to proactively render content to the user.