Dynamic Menu Adaptation via Controller Manipulation Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems for generating and presenting graphical user interfaces lack the ability to dynamically modify menus based on user interaction data, such as controller manipulation patterns, leading to inefficient user experiences and increased computational resources.
Innovation Solution
A system that utilizes controller manipulation data to select a profile identifier, which determines a subset of menu items to hide or show, modifying the menu in real-time based on user interaction patterns, thereby personalizing the user interface without explicit user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the system displays the complete menu of media streams, then the user has access to all available content, but the user must manually customize the menu which increases user effort and time
Solution Approach 1:
The system automatically analyzes controller manipulation data to identify user preferences and dynamically modifies the menu without requiring explicit user input. The system serves itself by inferring user needs from implicit interaction patterns, eliminating the need for manual menu customization while maintaining personalized content selection.
Solution Approach 2:
The system continuously monitors controller manipulation data as feedback about user interaction patterns. This feedback loop enables the system to learn user preferences over time and automatically adjust menu configurations, replacing manual customization processes with automated adaptive behavior based on observed user actions.
2Adaptability or versatility
If the system processes and stores detailed controller manipulation data, then the system can provide personalized menu modifications, but computational resources and data storage requirements increase
Solution Approach 1:
The system extracts only the essential features from raw controller manipulation data, such as directional patterns and interaction sequences, rather than processing every detail. This extraction approach maintains personalization capability while significantly reducing computational complexity and storage requirements by discarding redundant information.
Solution Approach 2:
The system performs preliminary processing of controller data to identify and store only the most relevant interaction patterns and user preference profiles. By preparing and filtering data in advance, the system reduces real-time computational burden while maintaining the ability to provide personalized menu modifications when needed.
Data Source
AI summary
A machine performs menu modification based on information that indicates how a controller device was manipulated by a user. The machine causes a media device to display a portion of a menu. The machine accesses controller manipulation data generated by a controller device in fully or partially controlling the media device, such as controller manipulation data that indicates a sequence of physical manipulations experienced by the controller device being operated by a user to select menu items. Based on the sequence of physical manipulations, the machine selects a profile identifier from a set of profile identifiers. Based on the profile identifier, the machine selects a first subset of the menu. The first subset indicates menu items to be hidden, unlike a second subset of the menu. The machine causes the media device to modify the menu by omitting the first subset while continuing to display the second subset.