App Recommendation UI Layout for Reducing Redundant Apps
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Solution Overview
Problem
As the number of apps increases, it becomes difficult for users to identify which apps are valuable, leading to confusion, unnecessary bandwidth usage, and inefficient storage, especially when apps have similar functionalities.
Innovation Solution
A user interface modification and recommendations system (UMS) that monitors user actions, generates a list of authorized, frequently used, and recommended apps, and rearranges the user interface to prioritize these apps, while removing duplicates and apps with overlapping functionalities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the volume of apps increases to provide more functionality and services, then the user can access more features, but it becomes increasingly difficult for the user to locate which apps are actually valuable
Solution Approach 1:
The system performs preliminary actions by pre-sorting and pre-organizing apps based on predicted user preferences before the user needs to locate them. The processor predicts which apps the user is most likely to use and pre-ranks them, so that when the user accesses the app list, the most relevant apps are already positioned at the top, eliminating the need for the user to search through a large volume of apps.
Solution Approach 2:
The system incorporates feedback mechanisms by monitoring user interactions with apps and adjusting the ranking over time. The processor receives feedback from user behavior patterns and refines the app prediction model accordingly, continuously improving the accuracy of which apps are presented first to the user.
2Adaptability or versatility
If apps with similar functionalities are included to provide comprehensive coverage, then the system offers more options, but it causes confusion and unnecessary bandwidth usage
Solution Approach 1:
The system extracts and removes duplicate or redundant apps from the presentation list. The processor identifies apps with substantially similar functionalities and selects only the most relevant one based on predicted user preferences, eliminating unnecessary duplicates that would cause confusion and waste bandwidth.
Solution Approach 2:
The system merges similar apps into a unified presentation by grouping apps with overlapping functionalities and selecting representative apps that best satisfy the user's needs. Instead of presenting multiple separate apps with similar functions, the system combines them into a streamlined list that maintains functional coverage while reducing redundancy.
3Adaptability or versatility
If all authorized apps are displayed to ensure comprehensive access, then the user has more choices, but it increases storage requirements and bandwidth usage
Solution Approach 1:
The system applies partial action by displaying only the subset of apps that the processor predicts the user is most likely to use, rather than displaying all authorized apps. This selective approach maintains adequate app accessibility for the user's needs while significantly reducing the quantity of app data that must be stored and transmitted.
Data Source
AI summary
Various embodiments for a user interface modification and recommendations system are described herein. An embodiment operates by displaying in a first section of a user interface a plurality of saved/favorite apps of a first user based on a list of saved/favorite apps of the first user. A list of authorized apps is generated from the first list of apps and comparing a user profile of the first user with permissions provided by the client system. A final list of recommended apps is generated by copying a preliminary list and removing all the saved/favorites apps of the first user. The first section of the user interface is updated by adding the at least one app from the final list of recommended apps to the first section.