Message Composition Engine Identifying Absent Context
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Solution Overview
Problem
Users often spend time composing messages as they may lack necessary details, leading to follow-ups for additional information, and conventional message templates are time-consuming to create and adapt to various scenarios.
Innovation Solution
A system that identifies and recommends missing context in messages during composition, using a message composition engine that analyzes the message type and compares context representations to provide recommendations for absent context, reducing the need for manual template selection and additional details.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional message templates are used, then message composition can be standardized, but they are time-consuming to create and adapt to various scenarios
Solution Approach 1:
The system automatically analyzes the message being composed, identifies absent context, and provides recommendations without requiring manual template selection or adaptation. The message composition engine performs self-service by autonomously detecting missing information and suggesting appropriate context based on the message type and content.
Solution Approach 2:
The system performs preliminary analysis of the message content before the user finishes composing, identifying absent context in advance. By proactively detecting missing information and providing recommendations during composition, the system eliminates the need for time-consuming template creation and adaptation afterward.
2Productivity
If messages are composed without additional details, then composition is faster, but follow-ups are needed to gather desired additional details
Solution Approach 1:
The system provides real-time feedback to the user during message composition by identifying absent context and recommending additional details that should be included. This feedback loop prevents incomplete messages from being sent, eliminating the need for follow-up communications to gather missing information.
Solution Approach 2:
The system performs preliminary identification of absent context before the message is sent, ensuring all necessary details are included in the initial composition. By detecting missing information in advance and prompting the user to add it, the system prevents the need for subsequent follow-up messages.
3Reliability
If comprehensive context is included in messages, then message completeness is improved, but message composition time increases
Solution Approach 1:
The message composition engine performs self-service by automatically analyzing the message content, determining the message type, and identifying absent context without requiring the user to manually ensure completeness. This automated analysis maintains message reliability while minimizing the time users need to spend on composition.
Solution Approach 2:
The system dynamically adjusts the level of context recommendation based on the identified message type and content parameters. By changing the parameters of what context is suggested and how prominently it is presented, the system ensures comprehensive messages are generated efficiently without uniformly increasing composition time for all messages.
Data Source
AI summary
Methods, computer systems, computer-storage media, and graphical user interfaces are provided for facilitating message composition, according to embodiments of the present invention. In one embodiment, message data associated with a message being composed is obtained. The message data is analyzed to determine a message type indicating a type of message and a message context representation representing a context provided within the message being composed. Context representations representing expected contexts associated with the message type of the message are identified. Thereafter, an absent context missing in the message being composed is determined based on a comparison of the message context representation with the set of context representations. A recommendation related to the absent context can be provided, for example, for display via a user interface.