Command Clustering for UI Adaptability
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Solution Overview
Problem
Users of software applications face difficulties in accessing and performing complex commands due to the vast number of available functions, leading to inefficient operation and lack of understanding, especially among lower-skill users.
Innovation Solution
The system processes and analyzes multiple commands to identify clusters based on coordinated usage, determining associations through confidence and support levels, and updates the user interface to present suggested commands or features, thereby enhancing user interaction and interface customization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If software applications include hundreds or thousands of different types of commands, then the functionality and versatility of the application is improved, but the ease of operation deteriorates because users cannot remember or understand how to access and perform certain commands
Solution Approach 1:
The system automatically analyzes user command sequences and generates contextual suggestions without requiring users to manually search for commands or receive external training. The interface serves itself by learning from user behavior patterns and presenting relevant commands proactively
Solution Approach 2:
The system monitors and analyzes user interactions with commands, using this feedback to identify coordinated usage patterns and generate contextual suggestions that adapt to individual user needs and improve ease of operation over time
2Loss of information
If the user interface presents all available commands, then completeness of information is improved, but the device complexity increases making the interface harder to navigate
Solution Approach 1:
The system extracts only the most relevant commands from the complete set of available commands based on analyzed user behavior patterns, presenting a simplified subset that maintains completeness of necessary information while reducing interface complexity
Solution Approach 2:
The interface provides different levels of command presentation based on local context - showing simplified views for common operations and providing access to complete functionality when needed, with suggestions tailored to specific user actions and contexts
3Productivity
If training is provided to users for complex commands, then the productivity is improved, but the loss of time increases due to the training requirement
Solution Approach 1:
The system performs preliminary analysis of user command sequences and prepares contextual suggestions in advance, so that when users need complex commands, the information is already available and ready, eliminating the need for separate training sessions
Solution Approach 2:
The system acts as an intermediary between the user and complex commands, providing contextual suggestions and guidance that bridge the knowledge gap without requiring formal training, thereby maintaining productivity while avoiding training time investment
Data Source
AI summary
Systems and devices for the evaluation and analysis of the usage of commands within user interfaces are disclosed. In an example, operations for clustering and analysis of commands performed in a user interface may include: processing data that identifies a set of commands used in a software application; identifying coordinated usage of respective commands of the set of commands; identifying clusters of commands based on the coordinated usage among the respective commands; defining associations within the clusters of commands based on relevancy, wherein the relevancy is determined for a respective cluster from clustering parameters such as a confidence value and a support level value; and identifying output features in the software application based on the clusters of commands. In a further example, the output features may include a presentation of a suggested command, or a change to a presentation of a user interface object.