Personalized User Interface Layout Adaptation

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Solution Overview

Problem

Conventional user interfaces are often cumbersome and non-intuitive, requiring significant time and effort for users to learn and adapt, leading to wasted time, reduced productivity, and a poor user experience due to inefficient organization of commands and options.

Innovation Solution

A learning-based personalized user interface system that utilizes machine learning to collect usage data and prioritize frequently used commands and options, hiding or de-prioritizing less frequently used ones, dynamically adjusting the layout based on user behavior and preferences.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If conventional user interfaces display all commands and options in a predetermined manner, then complete functionality is provided, but users experience overwhelming complexity and difficulty in locating frequently used commands

Engineering Contradiction:

Improveease of accessing frequently used commandsVSAvoidinterface complexity

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The user interface is segmented into multiple views or layers: a simplified default view showing only frequently used commands, and an expanded view revealing additional commands and options. This segmentation allows the interface to present information in manageable portions rather than overwhelming users with all commands simultaneously.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The interface dynamically adapts its complexity based on user needs and context. Frequently used commands are automatically promoted to prominent positions in the default view, while less frequently used commands are hidden or placed in expanded sections. The interface structure changes dynamically rather than remaining static.

Inventive Principle:

Principle #15Dynamics

2Adaptability or versatility

If users manually customize the display and ordering of commands, then personalization is achieved, but significant time and effort are required to determine and implement preferences

Engineering Contradiction:

Improveinterface personalizationVSAvoidtime to learn and customize interface

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system automatically monitors user interactions with commands and options, then self-adjusts the interface layout to reflect usage patterns. Frequently used commands are automatically moved to prominent positions without requiring user intervention. The interface serves itself by adapting based on observed behavior rather than waiting for manual customization.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system implements continuous feedback loops where user interactions with commands are tracked and analyzed. This feedback informs automatic reorganization of the interface, creating a closed-loop system that continuously adapts to user needs based on observed behavior patterns.

Inventive Principle:

Principle #23Feedback

3Adaptability or versatility

If users encounter new applications or updated versions, then new functionality is available, but users must undergo a learning process that wastes time and reduces productivity

Engineering Contradiction:

Improvecompatibility with new applications and updatesVSAvoidproductivity during learning period

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The system performs preliminary analysis of user behavior patterns early in the usage period, then proactively organizes commands and options to match emerging preferences. Rather than waiting for users to learn the interface through trial and error, the system anticipates needs and pre-arranges the interface optimally.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The interface parameters such as command ordering, visibility, and grouping are continuously changed based on usage data. The system transforms the interface configuration parameters dynamically to optimize for individual user patterns, allowing seamless adaptation to new applications and updates without requiring users to relearn fixed interface structures.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS10853100B1Systems and methods for creating learning-based personalized user interfaces

Publication Date: 2020.12.01 CADENCE DESIGN SYST INC

AI summary

Systems and methods for creating learning-based personalized user interfaces for software applications are described. Exemplary embodiments provide for collecting usage data and applying machine learning techniques to identify and prioritize certain commands and options in the personalized user interface. The usage data can include Usage patterns, usage sequences, and the usage of certain commands and options in connection with, or following, certain other commands and options may also be identified, and the personalization-based prioritization can include, for example, the contents, position, and quantities of the commands and options within the interface.