Feature Registry Deep Linking for Precise Cross-App Access
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Solution Overview
Problem
Conventional deep linking systems face challenges such as labor-intensive URL creation, lack of standardization, vulnerability to operating system updates, and complexity in handling contextual information, leading to inefficient and insecure user redirection.
Innovation Solution
A feature registry system that automatically updates and modifies links, reduces URL/URI complexity, and authenticates users, providing customized features through a machine learning model and feature template population.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If deep links are manually created for each URL to enable precise content access, then user navigation accuracy is improved, but the labor intensity and complexity of link creation increase exponentially
Solution Approach 1:
The patent introduces a feature registry as an intermediary system between URLs and deep links. Instead of manually creating deep links for each URL, the feature registry automatically maps URLs to features based on their content and functionality. This intermediary layer eliminates the exponential complexity of manual link creation while maintaining precise content access through automated feature identification and matching.
Solution Approach 2:
The system enables self-service deep link generation through automated feature detection and URL-to-feature mapping. The feature registry automatically analyzes URL content, identifies relevant features, and creates appropriate deep links without human intervention. This self-service mechanism resolves the contradiction by eliminating manual labor while preserving navigation precision through intelligent automation.
2Adaptability or versatility
If URL schemes are made more complex to support customization and contextual information, then user experience personalization is improved, but system vulnerability to operating system updates and modifications increases
Solution Approach 1:
The feature registry acts as a stable intermediary layer between the volatile URL schemes and the application features. Instead of making URL schemes complex and vulnerable, the system uses the feature registry to handle customization and contextual information. The registry maintains a stable feature catalog that is independent of operating system changes, while still supporting personalized user experiences through feature-based routing that remains reliable across system updates.
3Adaptability or versatility
If deep linking systems handle extensive contextual information (user preferences, link source, destination) to improve personalization, then user experience customization is enhanced, but processing time and system complexity increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and cataloging features in the feature registry before they are needed for deep linking. Features are pre-analyzed, tagged, and organized in advance, so that when a deep link is created or resolved, the system can quickly match URLs to features without extensive real-time processing. This preliminary preparation reduces processing delays while maintaining high personalization capabilities through pre-computed feature metadata and user preference profiles.
4Reliability
If feature registry implements real-time updates and authentication to ensure security and accuracy, then system reliability is improved, but computational overhead and processing time increase
Solution Approach 1:
The feature registry implements periodic authentication and validation rather than continuous real-time checking for all operations. Critical security points (feature registration, URL-to-feature mapping, user access) are authenticated periodically or on-demand, rather than continuously. This periodic approach maintains system reliability and security while reducing unnecessary computational overhead during routine operations, balancing accuracy requirements with energy efficiency.
Data Source
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AI summary
In some embodiments, 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. For example, the system may receive, at a server, a feature registry request from a feature registry application on a local device, wherein the feature registry request is generated by the local device in response to a user selection of hyperlinked content associated with the feature registry application. In response to receiving the feature registry request, the system may determine, at the server, whether a feature is available on a feature registry.