Game Progress-Based Content Recommendation System

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Solution Overview

Problem

Existing systems face challenges in recommending relevant content to video game users due to the vast and scattered nature of content items, high processing power requirements, and the difficulty in determining the optimal time for recommendations across multiple users and varied play times.

Innovation Solution

A system that receives video game performance data to identify challenges and recommends associated content by analyzing user performance data, utilizing a communication network to transmit relevant content for display, and aggregating gaming logs to integrate video game environments with other content sources, ensuring timely and relevant recommendations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If the system analyzes the vast universe of content items to identify relevant content, then content relevance improves, but processing power requirements increase

Engineering Contradiction:

Improvecontent relevance identificationVSAvoidprocessing power

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system segments the vast content universe into manageable categories (game-related content, entertainment content, tutorial content, etc.) and uses game event types to further segment content recommendations. This allows the system to analyze only relevant segments rather than the entire content space, reducing processing power while maintaining identification precision.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system performs preliminary actions by pre-categorizing content items and establishing content metadata structures in advance. Content items are pre-tagged with game identifiers, content types, and relevance indicators, so that during runtime, the system only needs to match game events with pre-processed content rather than analyzing all content from scratch.

Inventive Principle:

Principle #10Preliminary action

2Adaptability or versatility

If content items are stored in scattered locations across computer networks, then content availability increases, but content discovery difficulty increases

Engineering Contradiction:

Improvecontent availabilityVSAvoidcontent discovery

Core Design Contradiction:

Adaptability or versatilityVSDifficulty of detecting and measuring

Solution Approach 1:

The system introduces content metadata as an intermediary layer between scattered content items and game events. Metadata includes game identifiers, content type classifications, and relevance indicators that act as indexes, allowing the system to discover and retrieve relevant content from distributed locations without directly searching through all scattered content items.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Ease of operation

If the system recommends content at the right time for each user, then user engagement improves, but the complexity of determining optimal timing increases

Engineering Contradiction:

Improveuser engagementVSAvoidtiming determination system

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The system uses dynamic timing determination based on real-time game event detection. Instead of using fixed schedules or complex user behavior analysis, the system triggers content recommendations dynamically when specific game events occur (e.g., when a player completes a level, encounters a boss, or achieves a milestone), automatically aligning content delivery with the user's current gaming context.

Inventive Principle:

Principle #15Dynamics

4Measurement precision

If the system processes video game performance data from multiple users, then content recommendation accuracy improves, but data processing requirements increase

Engineering Contradiction:

Improverecommendation accuracyVSAvoiddata processing volume

Core Design Contradiction:

Measurement precisionVSQuantity of substance

Solution Approach 1:

The system extracts only the essential elements from video game performance data—specifically game event types and associated metadata—rather than processing entire gameplay sessions. By focusing on extracting and analyzing only the relevant event information needed for content matching, the system improves recommendation accuracy while minimizing data processing volume.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS20200306635A1Content recommendation based on game progress

Publication Date: 2020.10.01 ADEIA GUIDES INC

AI summary

Systems and methods for recommending content based on gaming progress are disclosed herein. Video game performance data, which is based on performance of a video game using a computing device, is received from the computing device over a communication network. Control circuitry determines, based on a criterion stored in memory, whether the video game performance data indicates a failure to overcome a challenge in the video game. In response to determining that the video game performance data indicates a failure to overcome the challenge in the video game, the control circuitry identifies for recommendation an item of content associated with the challenge and transmits a recommendation of the identified item of content for display via the computing device.