Dynamic Action Item Prioritization via Text Context
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Calendaring systems fail to capture dynamic changes in user tasks and activities, leading to static prioritization of action items that do not adapt to changing circumstances.
Innovation Solution
A method and system that dynamically re-prioritize and re-sort action items by automatically recognizing changes in task-related circumstances within electronically rendered texts, using natural language processing and machine learning to adjust priorities and expiry times based on multiple priority factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a calendaring system uses static prioritization of action items, then the system structure remains simple and stable, but the system fails to adapt to changing task circumstances
Solution Approach 1:
The patent implements dynamic prioritization by continuously monitoring task-related circumstances and automatically re-prioritizing action items based on changing conditions. The system transitions from static to dynamic prioritization, allowing action items to be automatically re-ranked as new information becomes available from sampled text sources, thereby resolving the contradiction between adaptability and system complexity.
Solution Approach 2:
The system employs feedback mechanisms by continuously sampling text sources to detect changes in task circumstances and using this information to re-compute priorities. This closed-loop feedback process enables the system to adapt to changing conditions automatically, improving adaptability while managing complexity through automated decision-making algorithms.
2Productivity
If the system dynamically re-prioritizes action items by monitoring multiple text sources, then task management efficiency improves, but computational resources and processing time increase
Solution Approach 1:
The system applies partial monitoring by selectively sampling text sources rather than continuously processing all available information. It identifies and monitors only the most relevant text sources and priority factors for each action item, reducing computational overhead while maintaining effective task management through targeted rather than exhaustive monitoring.
3Extent of automation
If the system automatically recognizes task changes from electronically rendered text, then the need for manual updates decreases, but the complexity of text processing and analysis increases
Solution Approach 1:
The system implements self-service automation by automatically sampling text sources, recognizing task-related changes, and re-prioritizing action items without requiring manual intervention. The automated text processing system independently monitors for changes, extracts relevant information, and updates priorities, reducing the need for user involvement while managing complexity through specialized natural language processing capabilities.
Data Source
AI summary
Dynamic prioritization of an action item can include retrieving an electronically rendered text from one or more sampled text sources in response to recognizing a user-related task conveyed within the electronically rendered text. Dynamic prioritization of an action item can also include generating an action item corresponding to the user-related task and prioritizing the action item by assigning to the action item a priority computed based on one or more priority factors corresponding to the user-related task. Each of the one or more priority factors can be automatically selected from a collection of predetermined priority factors. Additionally, dynamic prioritization of an action item can include recomputing the priority assigned to the action item in response to a change in task-related circumstances, as determined based on other electronically rendered text.