Topic Treatment Evaluation in Electronic Communications
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Solution Overview
Problem
Organizations face challenges in assessing the effectiveness of information dissemination through electronic communications, particularly in videoconferences and other non-written channels, as it is difficult to determine what information has been conveyed and how well it has been communicated.
Innovation Solution
A content management platform processes electronic communications using vector searches and large language models to evaluate the treatment of specified topics during meetings, assigning scores to the topic treatment and generating scorecards that correlate topic treatment with organizational goals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If electronic communications are used to distribute information, then information dissemination efficiency is improved, but the ability to assess communication effectiveness deteriorates
Solution Approach 1:
The system implements feedback by automatically analyzing meeting recordings to extract topic treatment information and comparing it against organizational goals. This creates a closed-loop system where communication effectiveness is continuously measured and fed back to improve future communications, resolving the contradiction between efficient information dissemination and the ability to assess its effectiveness.
Solution Approach 2:
The patent replaces manual assessment methods with automated AI-based analysis using large language models and vector searches. This substitution enables precise measurement of communication effectiveness across multiple channels without requiring manual review, thus maintaining high productivity while improving measurement precision.
2Adaptability or versatility
If multiple communication channels are used, then communication versatility is improved, but the difficulty of evaluating topic treatment deteriorates
Solution Approach 1:
The system achieves universality by creating a unified analysis framework that handles multiple communication channels (videoconferences, telephone calls, written communications) through the same AI-based topic extraction and evaluation process. This multi-functional approach enables consistent topic treatment evaluation across diverse communication modalities, resolving the contradiction between versatility and evaluation difficulty.
Solution Approach 2:
The patent introduces an intermediary layer (AI analysis system with large language models) that mediates between raw communication data from multiple channels and the evaluation process. This intermediary automatically transcribes, analyzes, and extracts topic treatment information from various communication formats, making evaluation feasible across diverse channels without increasing complexity for the end user.
3Measurement precision
If automated analysis is implemented, then measurement precision is improved, but device complexity deteriorates
Solution Approach 1:
The system implements self-service by enabling the AI analysis platform to automatically perform topic extraction, treatment evaluation, and scoring without requiring manual configuration or intervention. The system self-adjusts by learning from organizational goals and automatically adapting its analysis parameters, thus achieving high measurement precision while managing complexity through automation rather than manual processes.
Data Source
AI summary
A content management platform generates an interactive user interface that correlates (i) user interaction data associated with content items maintained by a content management platform, against (ii) treatment of topics during meetings that are recorded in meeting recording files stored by the content management platform. The platform assigns a topic assessment metric to meeting recording files by matching a vector representation of a portion of the file to a vector representation of a candidate topic. A scoring model can then be applied to the portion of the file to assess how the candidate topic was treated during the meeting. The platform can also capture use data that describes how users interact with information items maintained by the platform. A subset of this use data and the topic assessment metrics are populated into the user interface.