Text Communication Action Suggestion System
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Solution Overview
Problem
Existing systems lack the ability to automatically interpret and respond to textual communications by identifying relevant information and suggesting appropriate actions, such as creating calendar entries or generating directions, without user intervention.
Innovation Solution
A system that analyzes textual communications to identify descriptors like physical locations and temporal information, matches them with predefined templates, and suggests actions to the user, allowing for automatic generation of calendar entries or retrieval of directions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a system automatically interprets and responds to textual communications by identifying relevant information and suggesting actions, then productivity is improved, but device complexity increases
Solution Approach 1:
The system segments the textual communication processing into distinct components: identifier extraction module, template matching module, and action suggestion module. Each component handles a specific aspect of the processing pipeline, making the overall complex system manageable and maintainable while achieving high productivity through specialized processing for each function.
Solution Approach 2:
The patent introduces template structures as intermediary elements between raw textual communications and actionable responses. Templates serve as pre-defined patterns that bridge the gap between unstructured text and structured actions, simplifying the processing logic while enabling automated response generation across multiple communication types.
2Loss of time
If the system automatically generates calendar entries from textual communications, then time management is improved, but measurement precision requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-defining templates with expected information patterns before processing actual communications. These templates contain pre-specified fields for dates, times, locations, and other calendar-relevant data, allowing the system to automatically extract and structure information with high precision while saving user time on manual entry.
Solution Approach 2:
The system incorporates feedback mechanisms where extracted information is validated against template expectations, and users can provide feedback on extraction accuracy. This feedback loop continuously improves the precision of information extraction from textual communications, ensuring high-quality calendar entry generation over time.
Data Source
AI summary
A system, method, and computer-readable media are described for suggesting an action based on multiple descriptors within a textual communication (e.g. email, text message). In one embodiment, event descriptors within an email are identified and displayed to the email recipient with an indication that the descriptors are selectable. Upon receiving the selection of at least two descriptors, an action is suggested to the recipient for acceptance. Upon receiving the acceptance, the proposed action is performed.