Dynamic GUI Customization Using User Preferences and Third-Party Data
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Solution Overview
Problem
Existing graphical user interfaces (GUIs) lack customization options that leverage user preferences and third-party data to enhance accessibility and usability, leading to suboptimal user experiences.
Innovation Solution
A computing system and method that utilizes third-party coding and user inputs to customize GUI layouts based on user preferences and data from third-party databases, generating a prioritization list for enhanced user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a standardized GUI layout is used, then device complexity is reduced and ease of manufacture is improved, but adaptability to individual user needs deteriorates
Solution Approach 1:
The system pre-collects user preference data and third-party data before GUI customization is needed. User profiles are built in advance with labeled action data, and third-party databases are populated with relevant information. When customization is triggered, the system rapidly retrieves and processes this pre-prepared data to generate personalized layouts without requiring complex real-time analysis.
Solution Approach 2:
The patent introduces third-party databases as intermediaries that store and provide customization-relevant data. These databases act as mediators between user profiles and the GUI generation system, containing pre-processed information about user preferences, action labels, and customization parameters. This intermediary layer simplifies the customization process by providing ready-to-use data rather than requiring the system to extract and interpret raw data in real-time.
2Productivity
If third-party data and user preferences are integrated for customization, then user experience and operational efficiency are improved, but data processing complexity and time are increased
Solution Approach 1:
User preference data and third-party data are collected, labeled, and processed in advance before being needed for GUI customization. The system performs data preparation work beforehand, including labeling user actions and organizing third-party database contents, so that when customization is triggered, the data is already ready for rapid retrieval and application.
Solution Approach 2:
The patent replaces manual data processing and analysis with automated machine learning models and algorithms. These computational systems automatically analyze user behavior patterns, process third-party data, and generate customization parameters without human intervention. This substitution of mechanical/manual processes with automated computational processes significantly reduces the time required for data processing while maintaining high productivity.
3Measurement precision
If comprehensive user data collection is implemented, then customization accuracy and user benefits are improved, but system complexity and data management requirements are increased
Solution Approach 1:
Third-party databases serve as intermediaries that manage and organize comprehensive user data. These databases store pre-processed user profiles, labeled action data, and customization parameters, separating the complexity of data management from the GUI generation system. The intermediary databases handle data organization, validation, and retrieval, allowing the main system to focus on customization without being burdened by complex data management tasks.
Solution Approach 2:
The system transforms raw user data into standardized customization parameters through automated labeling and processing. User behavior data is converted into structured parameters that directly influence GUI layout decisions. This parameter transformation process maintains high measurement precision by systematically processing data through defined algorithms while reducing management complexity through standardization.
Data Source
AI summary
Systems and methods receive labeled action data of a user that would trigger customization of the standardized layout, wherein the labeled action data is labeled using (i) a classification method that incorporates third-party coding and (ii) one or more user inputs indicating the user's preferred action-based outcomes and is used for customizing the standardized layout. Existing selectable options for generating a customized GUI comprising a prioritization list are ascertained from user data of the user's profile, the customized GUI being different from the standardized layout. The prioritization list is generated according to rule(s) for derived benefits available to the user via use of each of the existing selectable options, the one or more benefits being derived, at least in part, by third-party databases and prior user actions. An update to the standardized layout that triggers display of the customized GUI is transmitted, via a network, to a user device.