Feature Registry for Universal Deep Linking Across Web and Mobile
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Solution Overview
Problem
Conventional deep linking systems face challenges such as labor-intensive URL creation and modification, increasing complexity due to user customization expectations, lack of standardization, and vulnerability to operating system updates.
Innovation Solution
The implementation of a feature registry that allows for easy updating and modification of links, reduces URL complexity, and automatically redirects users from inactive locations, while providing customized features through a modular and real-time approach.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional deep linking is used with manually created URLs, then specific content can be linked, but the system becomes labor-intensive and difficult to maintain as content changes
Solution Approach 1:
The system enables self-service through automated URL generation and management. The deep linking system automatically creates, updates, and maintains URLs based on content changes without requiring manual intervention, thereby maintaining linking accuracy while eliminating the labor-intensive nature of conventional URL management
Solution Approach 2:
The system performs preliminary action by pre-generating and caching URL mappings before they are needed. This allows the system to quickly resolve deep links without requiring manual URL creation at the moment of linking, reducing both the effort required and maintaining precision through pre-computed accurate mappings
2Adaptability or versatility
If URLs are made more complex to support user customization, then user experience improves, but system complexity increases
Solution Approach 1:
The system segments the URL structure into modular components that can be independently configured and managed. This allows customization capabilities to be added through separate modules rather than increasing overall URL complexity, enabling adaptability while maintaining system simplicity through structured segmentation
Solution Approach 2:
The system implements a universal deep linking framework that can handle multiple customization scenarios through a single standardized interface. This multi-functional approach allows the same URL structure to support various levels of customization without requiring separate complex URL schemes for each case, thereby improving versatility while controlling complexity
3Reliability
If deep linking systems are continuously updated to maintain active links, then user access reliability improves, but maintenance effort increases
Solution Approach 1:
The system implements automated feedback mechanisms that continuously monitor link status and content changes. When content is updated or moved, the system automatically receives feedback and updates the corresponding URLs without manual intervention, maintaining high link availability while eliminating the time-consuming manual maintenance required by conventional systems
Solution Approach 2:
The system maintains continuous operation by automatically detecting and responding to content changes in real-time. This continuous automated monitoring and updating ensures that deep links remain valid and functional without requiring periodic manual maintenance, thereby improving reliability while reducing the time investment needed
Data Source
AI summary
The methods and systems described herein improve upon existing deep linking concepts, by creating links directed to a feature registry which may then serve the user's need of selecting and accessing a given feature. The feature registry may provide customized features that may populate a feature template in a user interface (e.g., of a feature registry application) on a local device. This population may occur in both a real-time (e.g., based on a continuously updated machine learning model) and modular fashion. For example, the system and methods may generate customized content on a website or mobile application through a hyperlink by filtering available features on a feature registry based on the identity of the user, the information from the user profile, and the description of the hyperlink content.