Message Renotification for Critical Edit Detection
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Solution Overview
Problem
Messaging systems do not effectively renotify recipients of critical message edits made by senders, potentially leading to misunderstandings or errors if recipients only view the original, unedited message.
Innovation Solution
Implement a notification system that analyzes sent messages for viewing and edits, determining the criticality of changes and renotifying recipients if the edits are significant, using Natural Language Processing, Natural Language Classification, and Machine Learning to assess the impact of changes on the message's context.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system allows senders to edit sent messages, then message accuracy can be improved, but recipients may not be notified of critical edits leading to information loss
Solution Approach 1:
The system implements a feedback mechanism by monitoring message edits and sending renotifications to recipients when critical changes are detected. The notification system provides feedback to recipients about message modifications, ensuring they are aware of changes that affect message meaning or intent.
Solution Approach 2:
The patent introduces an intermediary notification system that mediates between the sender's edit actions and the recipient's message reception. This intermediary analyzes edits for criticality and selectively triggers renotifications, acting as a bridge to ensure important information is communicated.
2Loss of information
If the system renotifies recipients of all message edits, then information completeness is improved, but notification frequency increases causing user annoyance
Solution Approach 1:
The system applies local quality by differentiating between critical and non-critical edits. Instead of treating all edits uniformly, it selectively renotifies recipients only for critical changes that affect message meaning, timing, or actionability, while allowing non-critical edits to proceed without notification.
Solution Approach 2:
The patent changes the parameter of notification triggering from a binary edit-detection model to a criticality-based model. By introducing a criticality assessment dimension, the system adjusts notification behavior based on the significance of edits rather than simply their presence.
3Measurement precision
If the system analyzes message content to determine criticality of edits, then notification accuracy is improved, but system complexity increases
Solution Approach 1:
The system implements self-service by using automated natural language processing and machine learning models to autonomously analyze message content and determine edit criticality. The system serves itself by making intelligent decisions about notification necessity without requiring manual intervention or complex rule-based configurations.
Data Source
AI summary
In response to determining that an original message from a sender has been viewed by one or recipients of the original message, a determination is made whether the original message has been edited by the sender. In response to determining that the original message has been edited, another determination is made whether the edits are critical based, at least in part, on a change of context of the original message. In response to determining that the edits are critical, re-notifying the one or more recipients that the original message has been edited by the sender.