Predictive Interface Generation for Reduced Navigation Latency
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Solution Overview
Problem
Users face inefficiencies and poor user experiences when navigating through multiple interfaces of websites or programs, as they often need to load and interact with unwanted interfaces before reaching their desired ones, leading to unnecessary resource utilization and prolonged wait times.
Innovation Solution
A user device employs a machine learning-based interface generation platform that predicts the sequence of interfaces a user will navigate to, generating a GUI with links to these predicted interfaces, thereby reducing the need to load and interact with unnecessary interfaces, and utilizing a unified or story-time display configuration to present these links efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional interface navigation is used, then all interfaces are loaded and made available to users, but users spend time interacting with unwanted interfaces and resource utilization increases
Solution Approach 1:
The system performs preliminary actions by predicting the sequence of interfaces users will navigate to and pre-generating a customized interface containing only those predicted interfaces as links. This eliminates the need for users to load and interact with unwanted interfaces, directly reducing navigation time and resource utilization while maintaining adaptability through machine learning-based prediction
Solution Approach 2:
The system extracts only the relevant predicted interfaces from the complete set of available interfaces and presents them in a customized interface. By taking out and displaying only the interfaces users are predicted to need, the system reduces unnecessary interaction time while maintaining versatility through accurate prediction algorithms
2Ease of operation
If all interfaces are loaded for user access, then complete navigation options are provided, but processing and network resources are unnecessarily utilized
Solution Approach 1:
The system extracts and displays only the predicted interfaces that users are likely to access, rather than loading all available interfaces. This extraction approach maintains ease of operation by providing direct access to needed interfaces while significantly reducing processing and network resource utilization by eliminating unnecessary interface loads
3Productivity
If traditional interface loading is used, then all interfaces are available immediately, but user wait time and resource consumption increase
Solution Approach 1:
The system performs preliminary prediction of interface sequences and pre-generates customized interfaces containing only predicted interfaces. This preliminary action delivers interfaces more efficiently by avoiding the transmission and loading of unwanted interfaces, reducing network resource consumption while maintaining high productivity through accurate prediction
Solution Approach 2:
The system extracts only the necessary predicted interfaces from the complete interface set and delivers them to users. This extraction approach improves interface delivery efficiency by reducing the amount of data that needs to be transmitted and loaded, thereby reducing network resource consumption while maintaining productivity
Data Source
AI summary
A user device may provide, for display in a first area of a graphical user interface (GUI), a first link to a first predicted interface within a website or a program. The first predicted interface may be an interface to which a user is predicted to navigate. The first link may be a graphical representation of at least a portion of the first predicted interface. The user device may provide, for display in a second area of the GUI, additional links to additional predicted interfaces within the website or the program. The first link may be more prominently displayed in relation to the additional links. The additional predicted interfaces may be interfaces to which the user is predicted to navigate. The additional links may be graphical representations of at least a portion of the additional predicted interfaces.