Dynamic Task Menu Based on Navigation History
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing task tree systems are convoluted and time-consuming for users to navigate and select tasks, as they require manual navigation through a static list of tasks without dynamic updates based on user navigation history.
Innovation Solution
A method that dynamically updates the task tree menu using task navigation information to provide a suggestion list of likely subsequent tasks, sorted by transition counts, thereby streamlining the selection process by presenting a dynamic list of tasks that are frequently selected after a current task.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a static task tree menu is used, then the system structure is simple, but the time required for users to navigate and select tasks increases
Solution Approach 1:
The patent implements a dynamic task menu that automatically updates based on user navigation history. The system transitions from a static task list to a dynamic one that reorders tasks based on transition counts, presenting frequently accessed tasks higher in the list. This dynamic adaptation reduces navigation time while maintaining system manageability through automated updates.
Solution Approach 2:
The system incorporates feedback mechanisms by tracking user navigation patterns and using this information to update the task menu ordering. The system monitors which tasks users select after completing other tasks, calculates transition counts, and uses this feedback to optimize the task presentation order, creating a self-improving interface.
2Loss of time
If manual navigation through task tree is required, then the interface structure is simple, but the time consumed by users increases
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing transition counts between tasks based on historical user behavior. Before users need to navigate, the system has already analyzed navigation patterns and prepared an optimized task ordering, so when users access the task menu, they immediately see tasks in the most efficient order without having to manually search or navigate through convoluted structures.
3Productivity
If task list is not updated dynamically, then the system is easier to maintain, but user efficiency is reduced
Solution Approach 1:
The system implements self-service by automatically updating the task menu ordering without requiring manual intervention from administrators. The system autonomously monitors user navigation, calculates transition counts, and reorders tasks based on this data, eliminating the need for manual menu maintenance while continuously improving user efficiency through data-driven optimizations.
Data Source
AI summary
A device may receive task navigation information, identify a selection of a first task, of multiple tasks, based on the task navigation information, and provide a list of a group of tasks from the multiple tasks. The list of the group tasks may be based on information identifying tasks historically selected subsequent to the selection of the first task. The device may identify a selection of a second task, of the multiple tasks subsequent to identifying the selection of the first task; and store information identifying that the second task has been selected subsequent to the first task based on identifying the selection of the second task subsequent to the selection of the first task. The information identifying that the second task has been selected subsequent to the first task may include a number of times that the second task has been selected subsequent to the first task.