Relevance Alerting for Multi-Party Discussion Channels
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Solution Overview
Problem
In multi-party telecommunication discussions, participants often struggle to manage concurrent conversations, leading to missed dialogue and reduced user contribution due to irrelevant discussions.
Innovation Solution
A computer-implemented method generates relevance alerts by analyzing multi-party discussions based on user profiles, assigning relevance values, and triggering alerts when the value exceeds a threshold, ensuring participants are notified of relevant discussions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a participant monitors multiple concurrent multi-party discussions, then the individual can stay informed about various conversations, but the individual is likely to miss dialogue in respective discussions due to the inability to shift between conversations quickly enough
Solution Approach 1:
The system introduces an intermediary alerting mechanism that monitors multi-party discussions and notifies participants of relevant dialogue opportunities. The alerting system acts as a mediator between the discussion content and the participant, providing timely notifications that enable effective participation without requiring constant active monitoring of all concurrent discussions.
Solution Approach 2:
The patent replaces the mechanical approach of manually monitoring and shifting between multiple discussions with an automated computer-implemented system. The system automatically analyzes discussion content, determines relevance to the participant, and generates alerts, substituting human cognitive effort with automated information processing and notification mechanisms.
2Reliability
If alerts are generated for all multi-party discussion content, then the user receives comprehensive notifications, but the user is overwhelmed with irrelevant alerts
Solution Approach 1:
The system applies local quality by making alert relevance specific to each user based on their profile characteristics, discussion history, and participation patterns. Rather than generating uniform alerts for all users, the system tailors alert content and timing to match individual user needs and contexts, ensuring high relevance while reducing unnecessary notifications.
Solution Approach 2:
The system dynamically adjusts alert generation parameters such as relevance thresholds, notification timing, and alert frequency based on user behavior patterns and discussion context. By changing these parameters adaptively, the system maintains reliable alert delivery while preventing user overload from irrelevant notifications.
Data Source
AI summary
Techniques are described with respect to a system, method, and computer product for generating relevance alerts. An associated method includes analyzing a multi-party discussion based on a generated profile associated with a user and assigning at least one relevance value associated with the user to the multi-party discussion based on the analysis and an amount of multi-party discussion participation associated with the user. The method further includes generating an alert for the user to participate in the multi-party discussion in response to determining the relevance value exceeding a relevance threshold associated with the multi-party discussion.