Virtual Keyboard NLU Intent Analysis for Mobile Task Management
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Solution Overview
Problem
Users of mobile devices face challenges in managing and retaining actionable messages that require attention at a later time, as existing communication applications lack efficient mechanisms to automatically or guidedly manage messages with tasks or requests.
Innovation Solution
The implementation of a virtual keyboard application with natural language understanding (NLU) capabilities that analyzes messages to determine intent, allowing for the automatic setting of reminders or performing actions based on classified tasks or requests within messages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual management of actionable messages is used, then users have full control over message handling, but time loss and productivity decrease due to manual tracking of tasks and requests
Solution Approach 1:
The system automatically analyzes incoming messages using NLU to identify tasks and requests, then autonomously creates reminders and notifications without requiring user intervention. The mobile device serves itself by detecting actionable items and managing the reminder workflow independently
Solution Approach 2:
The system performs preliminary classification and analysis of messages to identify actionable items before the user needs to act on them. By pre-processing messages and creating reminders in advance, the system prepares the information in a ready-to-use format, reducing the time users spend on manual tracking
2Adaptability or versatility
If existing communication applications are used, then basic messaging functions are provided, but they lack automated mechanisms for managing tasks and requests requiring later attention
Solution Approach 1:
The virtual keyboard application integrates multiple functions: it serves as both a standard input method and an NLU-based message analysis system. The same application layer that handles text input also performs intent classification, task detection, and reminder creation, making the system multi-functional without requiring separate dedicated applications
Solution Approach 2:
The patent combines the virtual keyboard application with NLU capabilities and reminder management functions into a single integrated system. By merging message input, analysis, and action management into one application, the system enhances versatility while avoiding the complexity of multiple separate components
3Measurement precision
If natural language understanding analysis is performed on all messages, then accurate intent classification is achieved, but energy consumption increases
Solution Approach 1:
The system applies NLU analysis selectively rather than uniformly to all messages. By performing partial analysis on messages that are likely to contain actionable items and using heuristics to identify potential tasks and requests, the system achieves sufficient classification accuracy while reducing overall energy consumption compared to analyzing every message in detail
Data Source
AI summary
Systems and methods are described herein for performing actions based on a determined intent within messages received by a mobile device. In some embodiments, the systems and methods may access a message received by a mobile application (e.g., text messaging application, chat application, and so on) of the mobile device, analyze the message to determine an intent of the message (e.g., whether the message includes a request or a task for a recipient of the message), and perform an action based on the determined intent (e.g., set a reminder when the message includes a task for the recipient). Further details are described herein.