Electronic Messaging Intent Segmentation for Training Reliability
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Solution Overview
Problem
Existing electronic messaging systems face challenges in managing and processing messages due to ambiguity, noise, and varying information structures, which can hinder effective training and communication, especially in real-world scenarios where information is not always simple or structured.
Innovation Solution
A computer-implemented method that uses a knowledge base to determine message intents and generate electronic messages based on selected subsets or related intents, allowing for the modification of received messages to add ambiguity or provide incomplete information, thereby enhancing training sessions and ensuring secure data communication by masking sensitive information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-world information is used in electronic messaging, then training and communication reliability is improved, but message ambiguity and noise increase
Solution Approach 1:
The system segments real-world messages into structured components including intent identification, entity extraction, and context classification. By breaking down complex noisy messages into discrete elements, the system can process and train on the structured portions while filtering out ambiguity and noise, thus maintaining training reliability without sacrificing real-world message authenticity.
Solution Approach 2:
The patent introduces an intermediary processing layer that mediates between raw real-world messages and the training system. This intermediary layer performs intent recognition, entity extraction, and message reconstruction, transforming noisy real-world information into structured training data while preserving the essential communicative intent, thereby resolving the contradiction between using authentic messages and maintaining clarity.
2Measurement precision
If message intents are determined using a knowledge base, then message processing accuracy is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-building a knowledge base containing domain-specific information, entity relationships, and intent definitions before actual message processing occurs. This pre-computed knowledge structure enables accurate intent determination during runtime without requiring complex real-time reasoning, thus improving accuracy while managing system complexity through advance preparation.
Solution Approach 2:
The patent extracts essential intent-determination logic and knowledge from the complex message processing system into a separate, reusable knowledge base. By taking out the static knowledge component from the dynamic processing pipeline, the system achieves high accuracy through structured knowledge lookup while reducing the complexity of the active processing system.
3Productivity
If electronic messages are generated based on selected subsets of intents, then communication efficiency is improved, but information completeness may be reduced
Solution Approach 1:
The system applies local quality by selectively including or excluding specific intent components based on the communication context and requirements. Rather than uniformly processing all intents, the system identifies and processes only the locally relevant intents for each specific communication scenario, improving efficiency while preserving the necessary information completeness for that particular context.
Solution Approach 2:
The patent implements partial action by generating messages based on selected subsets of intents rather than processing all possible intents. This selective approach improves communication efficiency by focusing computational resources on the most relevant intents while still maintaining sufficient information completeness through intelligent selection of critical intent components.
Data Source
AI summary
The present disclosure relates to a method comprising receiving an electronic message. Message intents of the received electronic message and one or more related intents may be determined. An electronic message may be generated according to a selected subset of the message intents or according to the related intents. The generated electronic message may be provided.