Appstore-Timeline Recommendation System for Reliable App Discovery
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Solution Overview
Problem
Users face difficulty in acquiring high-quality information about smartphone applications (Apps) from application stores, as user comments often focus on the download process and refunds rather than the App itself, making it hard to find reliable information.
Innovation Solution
A service method and system that allows users to select Apps from an Appstore, upload timeline posts associated with the selected Apps, and share these posts with friends, weighting and ranking posts from friends with indirect personal relationships based on relationship level, interest, and favorite counts to provide reliable recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If user comments are collected from Appstore download pages, then a large amount of information can be acquired, but the quality of information is low because comments focus on download process and refunds rather than the App itself
Solution Approach 1:
The patent introduces a timeline service as an intermediary between users and the Appstore. Instead of directly collecting comments from the Appstore download page, the system redirects users to a timeline service where they can post reviews. This intermediary platform filters and organizes user feedback, ensuring that only relevant App-quality comments are collected, thus improving information quality while maintaining quantity.
2Adaptability or versatility
If posts from all users are displayed equally, then all user feedback is visible, but reliable recommendations are difficult to identify among unspecific user posts
Solution Approach 1:
The patent applies local quality by differentiating the display treatment of posts based on the uploader's identity. Posts from friends are displayed with higher prominence and weight compared to posts from other users. This selective differentiation allows the system to maintain inclusivity by displaying all posts while simultaneously improving recommendation quality by highlighting reliable sources.
Solution Approach 2:
The system changes the parameter of post visibility and weighting based on the relationship between the viewer and the uploader. By introducing a relationship-based weighting parameter, the system can dynamically adjust which posts are prioritized in the timeline, making reliable recommendations from friends more visible while still allowing all user posts to be viewed.
3Reliability
If friends' posts are weighted and ranked based on relationship level and interest, then reliable recommendations are provided, but the system complexity increases
Solution Approach 1:
The patent implements self-service by automatically calculating relationship levels and post weights without requiring manual intervention. The system automatically determines the relationship between users based on existing social network data, computes interest levels based on interaction history, and ranks posts accordingly. This automated approach reduces system complexity by eliminating the need for manual configuration while maintaining high recommendation reliability.
Data Source
AI summary
Exemplary embodiments provide a computer-implemented method of enabling a recommendation of a software to a user from a software marketplace based on activities of the user's friend of an internet-based social network who is related to the first user within the confines of the social network, said user maintaining an internet-based social network account, the method comprising: receiving, from the first user, a selection of an interface associated with the software marketplace, generating, by a computer-implemented recommendation system, a list of recommended software based on the internet-based social network into which the first user is logged into, sending the list of the of recommended software to the first user, wherein the computer-implemented recommendation system retrieves the information of the user's friend and assigns a weight to a post not displayed based on an attribute thereof.