Meeting Management System NLP Topic Analysis
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Solution Overview
Problem
Conventional meeting processes are inefficient, as participants often receive vague invitations and spend time wondering about the relevance of meeting content, leading to reduced engagement due to the lack of clear topic focus and optimized participant allocation.
Innovation Solution
A dynamic approach that analyzes meeting content to identify key topics, matches relevant profiles, and schedules meeting intervals based on these topics, allowing for targeted invitations and optimized participant allocation, with initial topic summaries provided at the start of the meeting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional meeting invitation processes are used, then meetings can be scheduled, but participants receive vague invitations and spend time wondering about relevance, leading to reduced engagement
Solution Approach 1:
The system performs preliminary analysis of meeting content and identifies relevant participants before the meeting is scheduled. By processing meeting summaries and matching them against user profiles in advance, the system ensures that only relevant participants are invited, eliminating the information gap about meeting relevance that plagues conventional invitation processes.
Solution Approach 2:
The patent introduces an intermediary system that acts as a bridge between meeting organizers and participants. This intermediary automatically analyzes meeting content, identifies relevant topics, matches them against user profiles, and generates targeted invitations with specific topic information, thereby resolving the information asymmetry in conventional meeting invitation processes.
2Productivity
If all potential participants are invited to meetings, then comprehensive coverage is achieved, but time and resources are wasted on irrelevant participants
Solution Approach 1:
The system applies local quality by customizing meeting invitations based on each participant's specific relevance to meeting topics. Instead of sending generic invitations to all potential participants, the system analyzes individual user profiles against meeting content and sends targeted invitations only to those with demonstrated relevance, thereby eliminating waste of time and resources on irrelevant participants while maintaining comprehensive coverage of actually relevant stakeholders.
Solution Approach 2:
The patent changes the parameter of participant selection from a static, broad-based approach to a dynamic, relevance-based approach. By continuously analyzing meeting content and matching it against user profiles, the system dynamically adjusts which parameters define eligible participants, ensuring that only those with actual relevance to specific meeting topics are invited, thus optimizing meeting efficiency and reducing time waste.
3Loss of information
If detailed topic information is provided in meeting invitations, then participant relevance is improved, but processing and management complexity increases
Solution Approach 1:
The system implements self-service by automatically analyzing meeting summaries, extracting topics, matching them against user profiles, and generating personalized invitations with relevant topic information. This automated self-service approach provides detailed topic information to improve participant relevance while avoiding the complexity burden on human organizers, as the system handles the processing and management tasks autonomously.
4Ease of operation
If meetings are scheduled with fixed time windows, then scheduling simplicity is maintained, but flexibility to accommodate participant availability and topic depth is reduced
Solution Approach 1:
The patent applies segmentation by dividing meetings into multiple time intervals, each dedicated to specific topics. This segmentation allows the overall meeting to maintain a fixed schedule while individual topic intervals can be flexibly adjusted based on participant availability and topic depth requirements. The segmented structure preserves scheduling simplicity at the macro level while enabling adaptability at the micro level of individual topic discussions.
Data Source
AI summary
One example method of operation may include identifying a proposed meeting summary, processing proposed meeting summary content of the proposed meeting summary to identify topics to apply to a meeting, creating the meeting to include meeting time intervals, assigning one or more of the topics to one or more of the meeting time intervals, identifying profiles of user accounts matching one or more of the topics, assigning the user accounts, with profiles matching one or more of the topics, to one or more of the meeting time intervals with assigned ones of the topics which match the profiles of the user accounts, transmitting meeting invites to the user accounts, and initiating the meeting at a scheduled time.