Adaptive Page Layout Server for User Interface Optimization
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Solution Overview
Problem
Existing cloud platform user interface layouts often fail to present relevant information efficiently, leading to degraded user experience and reduced efficiency due to manual design limitations, where the creator may not fully understand the use cases for all users, resulting in increased latency and unnecessary user interactions.
Innovation Solution
A page layout server that tracks user interactions and employs data mining and machine learning techniques to analyze usage patterns, determining and updating user interface layouts tailored to specific user roles or groups, optimizing the display of relevant information and reducing system latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a user manually builds a page layout, then the layout can be customized according to the builder's understanding, but the layout may fail to present relevant information and degrade user experience because the builder may not fully understand use cases for all users
Solution Approach 1:
The system tracks user interactions with the page layout including clicks, time spent on components, and navigation patterns. This feedback is continuously collected and used to automatically adjust and optimize the layout, ensuring it adapts to actual user behavior rather than relying solely on manual configuration by potentially uninformed builders.
Solution Approach 2:
The system employs machine learning algorithms that automatically analyze usage patterns and generate optimized layout configurations without requiring manual intervention. The layout serves itself by using its own usage data to improve its own structure, eliminating the need for builders to have deep understanding of all user cases.
2Device complexity
If a manual page layout is created, then the layout structure can be controlled by the builder, but the layout may introduce latency and reduce system efficiency due to unnecessary user interactions
Solution Approach 1:
The system replaces manual layout design mechanics with automated machine learning-based optimization. Instead of relying on human builders to intuitively structure layouts, the system uses algorithms that objectively analyze usage data and determine optimal component arrangements, reducing unnecessary interactions and latency.
Solution Approach 2:
The system dynamically adjusts layout parameters such as component positioning, visibility, and hierarchy based on analyzed usage patterns. High-priority components are positioned for easier access, and low-priority components are minimized or hidden, thereby reducing the number of interactions users must perform and decreasing system latency.
3Quantity of substance
If an updated page layout is generated manually, then the layout can be modified to include additional information, but the layout may present unrelated or unhelpful information that reduces user efficiency
Solution Approach 1:
The system applies different levels of information detail and prominence to different parts of the layout based on local usage patterns. Components that are frequently accessed or important for specific user roles are enhanced with more detailed information, while less important components are simplified. This ensures relevant information is prominently displayed without overwhelming users with unrelated content.
Solution Approach 2:
The layout dynamically adapts its information content based on user behavior patterns. The system continuously monitors which components and data elements are most useful to different user groups and adjusts the layout accordingly, ensuring that the right information is presented to the right users at the right time, thereby maintaining high user efficiency.
Data Source
AI summary
Methods, systems, and devices supporting adjusting user interfaces based on user usage patterns are described. A page layout server may store an initial page layout for a page corresponding to a data object type, where the initial page layout may be defined by a first user and include a set of user interface components. The page layout server may transmit, to a set of user devices, a first indication of the page for display by the set of user devices according to the initial page layout. The page layout server may track user interactions with the set of user interface components, determine an updated page layout for the page based on an analysis of the tracked user interactions and the initial page layout, and transmit a second indication of the page for display by the set of user devices according to the updated page layout.