Game Performance Metric Video Recommendation System
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Solution Overview
Problem
Users face challenges in finding relevant and optimal video tutorials for improving specific aspects of their video game performance, as they need to sift through numerous user-uploaded videos.
Innovation Solution
A system that utilizes a streaming game server to store and index video game performance videos by parameters such as game title, level, and performance metrics. The server recommends optimal tutorial videos based on the user's current or upcoming game level and performance metrics, either by selecting the best video for a specific metric or stitching together clips for multiple sub-levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users manually search through vast amounts of user-uploaded videos to find helpful tutorials, then they can find relevant content, but the time and effort required to locate optimal videos increases significantly
Solution Approach 1:
The patent introduces an intermediary system (video recommendation system with performance metric analysis) that mediates between the user and the vast library of user-uploaded videos. The system automatically analyzes user gameplay performance metrics, compares them against metrics from video tutorials, and recommends optimal videos without requiring manual searching, thus resolving the contradiction between finding relevant content and spending time doing so
Solution Approach 2:
The system enables self-service by automatically performing the video selection task that would otherwise require manual user effort. The system autonomously captures performance metrics, processes them through comparison algorithms, and generates recommendations without user intervention in the search process, eliminating the time loss while ensuring relevant content is found
2Adaptability or versatility
If the system indexes and stores all user-uploaded videos with their performance metrics, then comprehensive video recommendations can be provided, but the system complexity and storage requirements increase
Solution Approach 1:
The patent applies local quality by making the video indexing and storage adaptive to specific needs. Rather than uniformly processing all videos, the system selectively indexes videos based on their relevance to user performance goals and the specific game/level/metric combinations. This targeted approach provides comprehensive recommendation capability where needed while reducing unnecessary storage and processing complexity elsewhere in the system
3Measurement precision
If the system analyzes multiple performance metrics to select optimal videos, then recommendation accuracy improves, but the computational processing time increases
Solution Approach 1:
The system applies preliminary action by pre-processing and organizing video data during upload, including extracting and storing key performance metrics in an accessible format. This preliminary organization of multiple metrics allows for rapid comparison and selection during the recommendation phase, maintaining high measurement precision while reducing the computational time required at the moment of video selection
Data Source
AI summary
Systems and methods for recommending video game content based on video game performance are disclosed. A level is identified from among a sequence of playable levels of a currently active video game. A video game performance metric for the identified level is determined. Based on the determined video game performance metric, a video of a performance of the identified level of the video game is selected for recommendation from among a plurality of videos stored in a database in association with corresponding video game performance metrics. An option, which is selectable to cause playback of the selected video, is transmitted for display via a computing device.