Dynamic Meeting Agenda Generation via Expert Weighting

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Solution Overview

Problem

Business meetings often lack efficient agenda planning, leading to inefficiencies and productivity losses, as many meetings are not well-organized, with a significant portion of time spent on irrelevant topics and only a third lacking an agenda altogether, despite the importance of clear objectives and agendas for success.

Innovation Solution

A system for dynamic agenda generation based on content discussions and expert assessment, utilizing natural language processing, sentiment recognition, and machine learning to create a prioritized list of discussion topics, assigning weights to experts, and optimizing meeting schedules to maximize importance and time utilization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional meeting planning methods are used, then meetings can be scheduled, but they lack structured agendas and clear objectives, leading to inefficiency

Engineering Contradiction:

Improvemeeting efficiencyVSAvoidtime spent on irrelevant topics

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by automatically generating agendas before meetings occur. It processes content discussions, identifies relevant topics, and creates structured agendas in advance, ensuring that meeting participants have a clear roadmap of what will be discussed and why, thereby preventing time waste on irrelevant topics during the actual meeting

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system enables self-service by automatically generating and optimizing agendas without requiring manual intervention from meeting organizers. It autonomously processes discussions, applies expert assessments, and creates finalized agendas, freeing participants from the tedious task of manual agenda creation while maintaining high structural quality

Inventive Principle:

Principle #25Self-service

2Ease of operation

If manual agenda creation is used, then agendas can be customized, but they are time-consuming and lack optimization

Engineering Contradiction:

Improveagenda creation easeVSAvoidtime for agenda preparation

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system performs self-service by automatically processing content discussions, applying natural language processing, and generating optimized agendas without requiring manual input from users. This eliminates the time-consuming manual creation process while maintaining high customization through AI-driven topic selection and structuring

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system replaces the mechanical manual agenda creation process with automated AI-based processing. It uses natural language processing, sentiment recognition, and machine learning algorithms to automatically analyze discussions and generate structured agendas, substituting human manual labor with intelligent automation that is both faster and more consistent

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Manufacturing precision

If expert assessment is incorporated, then agenda quality improves, but the complexity of the system increases

Engineering Contradiction:

Improveagenda qualityVSAvoidsystem complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The system introduces an intermediary layer of AI processing that bridges raw content discussions and final agenda generation. This intermediary layer automatically processes discussions, applies expert assessments, and translates them into structured agendas, maintaining high quality while managing complexity through automated mediation rather than direct human expert intervention

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system substitutes manual expert assessment with automated AI-based evaluation mechanisms. It uses natural language processing and machine learning models to automatically analyze discussion content, determine topic importance, and generate optimized agendas, replacing the complexity of human expert review with programmable algorithms that scale consistently

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS11757669B1Asynchronous dynamic generation of meeting agendas based on content discussions and expert assessment

Publication Date: 2023.09.12 DAOMMO INC

AI summary

Generating an agenda for a meeting includes creating a content repository that includes content corresponding to feedback from previous targeted meetings and/or information corresponding to ongoing discussions between potential attendees of the meeting, automatically creating a prioritized list of discussion topics, and at least one expert providing gestures to a computer screen to create an assessment for the discussion topics, display additional data for the prioritized list of the discussion topics, and/or transfer one or more of the discussion topics of the prioritized list of the discussion topics to either a list of dropped discussion topics or to an ordered list of selected discussion topics. An agenda is automatically generated based on the ordered list of selected discussion topics and on weights assigned to the at least one expert according to relative expertise. An order of agenda items is based in part on the weights.