Simultaneous Message Delivery via NLP Similarity Thresholds
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Solution Overview
Problem
Conventional messaging and chat systems do not provide a way for participants to have their responses presented simultaneously, which can lead to outside influences affecting the responses of other participants in a conversation.
Innovation Solution
A method and system that uses natural language processing to determine similarity scores for messages from multiple users, allowing messages to be transmitted and displayed simultaneously only when the scores exceed a predetermined threshold, and alerting users if messages are dissimilar.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional messaging systems transmit messages immediately as they are received, then message transmission speed is improved, but message integrity and simultaneity are compromised
Solution Approach 1:
The system performs preliminary actions by receiving and storing messages from multiple users in a buffer before transmission, analyzing their similarity, and only then transmitting them simultaneously. This preliminary buffering and analysis phase ensures that messages are transmitted together as a coordinated group, maintaining integrity while enabling fast simultaneous delivery.
Solution Approach 2:
The system provides a cushioning mechanism by implementing a message buffer that temporarily holds messages before transmission. This buffer acts as a cushion that absorbs timing variations and allows the system to wait for additional similar messages, ensuring simultaneous transmission without compromising the overall speed of the messaging system.
2Reliability
If the system waits for similarity analysis before transmitting messages, then message integrity is improved, but transmission delay increases
Solution Approach 1:
The system applies partial action by analyzing only the necessary aspect of messages (similarity based on keywords and topics) rather than performing complete semantic analysis. This partial analysis approach provides sufficient similarity assessment to ensure meaningful simultaneous transmission while minimizing the time delay caused by analysis.
Solution Approach 2:
The system changes the analysis parameter from comprehensive semantic understanding to keyword and topic-based similarity scoring. This parameter change enables faster message comparison and similarity determination, reducing transmission delay while still ensuring that transmitted messages are sufficiently similar to warrant simultaneous delivery.
3Measurement precision
If the system implements natural language processing for message similarity, then message selection accuracy is improved, but system complexity increases
Solution Approach 1:
The system segments the natural language processing task into distinct components: keyword extraction, topic identification, and similarity scoring. By dividing the NLP process into these manageable segments, the system achieves accurate message similarity assessment while keeping each component's complexity manageable and independent.
Solution Approach 2:
The system introduces an intermediary similarity scoring mechanism that bridges the gap between raw messages and transmission decisions. This intermediary layer processes messages through keyword and topic analysis, providing a quantitative similarity metric that simplifies the decision-making process while maintaining high measurement precision.
4Ease of operation
If the system transmits messages simultaneously, then user experience is improved, but coordination complexity increases
Solution Approach 1:
The system merges multiple individual message transmissions into a single coordinated transmission event. By combining messages that pass the similarity threshold into one simultaneous delivery, the system improves user experience through coordinated presentation while managing coordination complexity through automated similarity-based grouping logic.
Data Source
AI summary
Methods and systems for simultaneous message blocking and delivery are disclosed. A method includes: receiving, by a computing device, from a first user, a first message and a request to transmit the first message as a simultaneous message; receiving, by the computing device, an additional message from each of at least one additional user; determining, by the computing device, using natural language processing, a similarity score for each of the additional messages; and in response to the similarity score for each of the additional messages exceeding a predetermined threshold, the computing device transmitting the first message and the additional messages.