Ambiguous String Summarization for Instant Messaging
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Solution Overview
Problem
Current instant messaging systems generate cluttered notifications and hinder work prioritization due to multiple notifications for multiple messages or long messages in 1:1 conversations, especially when messages contain ambiguous elements like emojis and acronyms that change meaning based on context and sentiment.
Innovation Solution
A processor analyzes unread messages to generate an ambiguous strings model through topic modeling, linguistic analysis, sentiment analysis, and text summarization, creating a concise summary that accounts for unconventional characters and context, enabling the creation of a single, meaningful notification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple notifications are generated for multiple unread messages, then the user receives complete information about all messages, but notification clutter increases and work prioritization is hindered
Solution Approach 1:
The patent combines multiple unread messages into a single notification by generating a consolidated summary that includes the most relevant information from all messages. This merging approach reduces notification clutter while preserving essential message content through intelligent summarization that prioritizes important information.
Solution Approach 2:
The system extracts and prioritizes the most important information from multiple messages, pulling out key elements such as urgent keywords, important entities, and critical details. This extraction process allows the single notification to convey essential information without including all message content, thereby reducing clutter while maintaining information completeness.
2Object-generated harmful factors
If a single-line preview is shown for long messages, then notification clutter is reduced, but the user cannot recognize the full topic or essence of the message
Solution Approach 1:
The notification system dynamically adjusts the summary length and detail level based on message characteristics, conversation context, and user preferences. This dynamic approach allows the single notification to adaptively convey the appropriate amount of information for topic recognition while maintaining a compact format that avoids clutter.
Solution Approach 2:
The system changes parameters such as summary length, information density, and content selection based on the specific message properties and user needs. By adjusting these parameters, the notification can provide sufficient topic recognition information within a single-line or compact format, resolving the contradiction between brevity and information completeness.
3Productivity
If conventional text summarization is used without context awareness, then processing is simpler and faster, but ambiguous elements like emojis and acronyms are misinterpreted
Solution Approach 1:
The patent introduces an intermediary context-aware processing layer that sits between conventional summarization algorithms and the final output. This intermediary layer interprets ambiguous elements like emojis and acronyms by analyzing conversation context, sentiment, and message history before passing information to the summarization engine, ensuring accurate interpretation while maintaining processing efficiency.
Solution Approach 2:
The system performs preliminary analysis of ambiguous elements, emojis, and acronyms before the main summarization process. By pre-processing and resolving ambiguities in advance using context from conversation history and sentiment analysis, the system ensures accurate interpretation without significantly impacting overall processing speed during the summarization phase.
4Loss of information
If notifications include detailed message content, then the user can understand message essence without opening each message, but the notification becomes too long and loses its preview function
Solution Approach 1:
The notification includes a partial summary that focuses on the most essential information from each message, rather than attempting to convey complete message content. This partial action approach selects and presents only the critical elements needed for message essence understanding, keeping the notification length manageable while maintaining its preview function.
Solution Approach 2:
The notification content is segmented into hierarchical levels of importance, with the most critical information displayed prominently and additional details available on demand. This segmentation allows the notification to convey message essence through structured, prioritized information while maintaining a compact format that preserves the preview function.
Data Source
AI summary
A processor may analyze one or more unread messages. The one or more unread messages may be from one or more respective conversations. The processor may generate, from the analyzing, an ambiguous strings model. The processor may summarize, via utilization of the ambiguous strings model, the one or more unread messages. The processor may genericize the ambiguous strings model.