Meeting Divergence Detection via Contribution Linkage Analysis
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Solution Overview
Problem
Meetings often diverge from their core intent due to conversations deviating from intended topics, leading to inefficiencies and participant frustration, as existing approaches focus on participant mindset rather than contributions relative to core intents.
Innovation Solution
A method and system that monitor meeting contributions, determine linkages between them based on participant expertise and characteristics, and generate graphical representations to identify divergence from core intents, facilitating remedies such as inviting relevant participants to address gaps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing approaches focus on participant mindset to manage meeting divergence, then participant engagement may be maintained, but the ability to detect and correct actual divergence from core intents deteriorates
Solution Approach 1:
The patent replaces subjective mindset-based monitoring with an automated natural language processing system that objectively analyzes meeting transcripts. The system uses computational algorithms to compare spoken contributions against predefined core intents, automatically detecting divergence without relying on human judgment or manual tracking of participant engagement.
Solution Approach 2:
The patent introduces an intermediary system that acts as a bridge between meeting participants and core intents. This system processes contributions through NLP, compares them against intended topics, and provides feedback to facilitators, thereby mediating the detection and correction of divergence while maintaining participant engagement.
2Ease of operation
If manual tracking of meeting contributions is used to monitor divergence, then participant engagement is maintained, but productivity and efficiency deteriorate due to time consumption
Solution Approach 1:
The meeting management system performs self-service by automatically analyzing contributions and detecting divergence without requiring manual intervention. The NLP system processes transcripts, identifies off-topic discussions, and alerts facilitators, freeing participants to focus on the meeting content rather than tracking progress manually.
Solution Approach 2:
The patent replaces manual tracking mechanisms with automated computational analysis. Natural language processing algorithms continuously monitor meeting transcripts, compare contributions against core intents, and generate divergence alerts, eliminating the time-consuming manual tracking process while maintaining engagement through automated feedback.
3Productivity
If automated systems are introduced to detect meeting divergence, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent implements a multi-functional system that performs transcript analysis, divergence detection, facilitator alerts, and gap identification through a single integrated NLP-based platform. This universal approach consolidates multiple meeting management functions into one system, improving productivity without proportionally increasing complexity.
Solution Approach 2:
The system incorporates feedback mechanisms where automated divergence detection triggers alerts to facilitators, who can then intervene to redirect discussions. This feedback loop enables efficient meeting management through automated monitoring while keeping the system complexity manageable by focusing on the critical function of divergence detection and alerting.
4Measurement precision
If detailed analysis of each contribution is performed to detect divergence, then measurement precision is improved, but loss of time increases due to processing overhead
Solution Approach 1:
The patent uses natural language processing and computational algorithms to automatically analyze contributions in real-time or near-real-time. The system extracts key topics from transcripts, compares them against core intents using semantic analysis, and detects divergence without manual review, achieving high precision while minimizing processing time through automated computational methods.
Data Source
AI summary
A method, a computer program product, and a computer system manage meeting divergence for a meeting involving a plurality of participants to discuss a plurality of core intents. The method includes receiving a first contribution from a first one of the participants during the meeting. The method includes determining a first one of the core intents that the first contribution is associated. The method includes determining a linkage of the first contribution to at least one second, previous contribution provided during the meeting. The method includes generating a graphical representation of a progress of the meeting, the graphical representation including a first visual indicator corresponding to the first contribution and at least one second visual indicator respectively corresponding to the at least one second contribution. The first visual indicator is positioned with respect to the at least one second visual indicator to represent the linkage.