AI To-Do List Generation via Device Operation Analysis
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Solution Overview
Problem
Users face difficulties in effectively managing their tasks across various devices and service providing servers, leading to inefficiencies in checking and completing to-do lists, as existing systems lack advanced technologies to analyze operations and generate personalized task lists.
Innovation Solution
A system and method utilizing AI technology, specifically deep learning, to analyze user device operations, generate keyword lists from various applications, and provide a graphical user interface for editing and displaying candidate tasks, allowing for task replacement and performance monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually manage tasks across various devices and service providing servers, then task management can be performed, but it becomes difficult for users to effectively check their own tasks and requires significant time and effort
Solution Approach 1:
The system automatically generates to-do lists by analyzing user device operations and service data without requiring manual user input. The processor autonomously extracts tasks from application data, determines keywords, and creates personalized to-do lists, enabling the system to serve itself in task generation rather than relying on manual user management
Solution Approach 2:
The system proactively generates to-do lists before users need to check them by continuously analyzing device operations and service data in the background. Tasks are prepared and organized in advance, so users can directly view completed to-do lists without spending time on manual task creation or checking
2Adaptability or versatility
If existing rule-based smart systems are used, then basic automation can be provided, but they lack the capability to effectively analyze user operations and generate personalized task lists
Solution Approach 1:
The system transitions from rule-based parameters to AI-driven parameters by using machine learning algorithms to analyze device operations. The processor determines keywords and generates tasks based on learned patterns from user behavior data, service data, and application usage, enabling dynamic personalization that adapts to individual user preferences and habits
Solution Approach 2:
The patent replaces rule-based mechanical systems with AI-based cognitive systems. Instead of following predetermined rules, the system uses deep learning and machine learning algorithms to automatically understand user operations, infer task intentions, and generate personalized to-do lists, substituting rigid mechanical automation with adaptive intelligent automation
3Ease of operation
If users need to edit and customize task lists, then flexibility can be provided, but it increases the complexity of the system and requires additional user interaction
Solution Approach 1:
The system creates keyword lists and candidate task lists as simplified copies or representations of the full task management system. Users interact with these lightweight lists for editing and customization rather than dealing with the complete system complexity, making the interface easier to use while maintaining backend sophistication
Solution Approach 2:
The system divides the task management process into separable components: keyword determination, candidate task generation, and final task list creation. Users can edit specific segments (keywords or candidate tasks) independently without affecting the entire system, reducing perceived complexity while maintaining flexibility
Data Source
AI summary
Provided are a system and/or method of providing a to-do list of a user. A device for providing a to-do list of a user may include: a communicator configured to communicate with an external device; a display; and a processor configured to determine at least one keyword used to determine at least one task to be performed by the user in the to-do list, based on data obtained by an application executed on the display, generate a keyword list of the determined at least one keyword, and display a graphical user interface (GUI) for selecting at least one of the at least one keyword in the keyword list by controlling the display.