Flow Autocomplete System for UI Navigation
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Solution Overview
Problem
Users often have to perform multiple interactions and selections to navigate to specific locations within a user interface, which can be time-consuming and inefficient.
Innovation Solution
Implementing a flow autocomplete system that monitors user interactions and suggests locations based on frequent navigation patterns, allowing users to select links that execute the necessary steps to reach desired positions within the user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional manual navigation through multiple user interface steps is used, then users can reach specific locations within the user interface, but the process is time-consuming and requires multiple interactions
Solution Approach 1:
The system performs preliminary actions by monitoring and recording user interaction sequences in advance. When a user starts a new interaction sequence, the system compares it against previously recorded sequences to predict the user's destination and proactively presents autocomplete suggestions, thereby performing the navigation prediction action before the user completes all manual steps.
Solution Approach 2:
The patent introduces an intermediary autocomplete suggestion system that mediates between the user's current interaction and the final destination. Instead of directly navigating through all intermediate steps, the user interacts with the autocomplete interface which presents predicted locations, and selecting a suggestion automatically executes the intermediate navigation steps, thus the autocomplete system acts as an intermediary that shortcuts the manual navigation process.
2Productivity
If multiple manual steps are required to navigate through the user interface, then precise location access is achieved, but user efficiency decreases
Solution Approach 1:
The system extracts the essential navigation intent from partial user interactions by analyzing sequences of interface steps. Instead of requiring users to complete all interface steps manually, the system extracts the predicted destination location from the interaction pattern and presents it as an autocomplete suggestion, thereby taking out the redundant intermediate steps from the user's task.
Solution Approach 2:
The patent uses copying by recording and storing sequences of user interactions and their corresponding destination locations. When a similar interaction pattern is detected, the system copies the predicted destination from previously recorded sequences and presents it as an autocomplete suggestion, allowing users to reach frequently visited locations without repeating the full navigation sequence.
3Loss of time
If the system monitors and analyzes user interactions to provide autocomplete suggestions, then navigation time is reduced, but system complexity increases
Solution Approach 1:
The patent applies universality by designing the interaction monitoring system to serve multiple functions: it not only collects data for autocomplete suggestions but also adapts to different user interfaces, tracks various interaction types (clicks, hovers, keyboard input), and provides suggestions across different contexts. This multi-functionality reduces the need for separate systems for each navigation task, thereby managing complexity while improving navigation time.
Solution Approach 2:
The system implements feedback by continuously monitoring user interactions and using this information to generate and refine autocomplete suggestions. The feedback loop involves comparing actual user navigation patterns against predicted suggestions, learning from discrepancies, and improving prediction accuracy over time. This feedback mechanism enables the system to reduce navigation time adaptively without requiring complete redesign for each new usage scenario.
Data Source
AI summary
In one implementation, a system for protocol determination includes a monitor engine to monitor a number of interactions with a user interface. In addition, the system includes a sequence engine to determine a plurality of steps for each of the number of interactions. In addition, the system includes a reference engine to determine a step from the plurality of steps that corresponds to at least one of the number of interactions. In addition, the system includes a selection engine to suggest a particular interaction with the user interface based on the determined first step.