Adaptive Content Recommendation System for Network-Constrained Streaming

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Solution Overview

Problem

Existing content streaming technologies face challenges in recommending and streaming media content with optimal resolution due to varying network conditions, as devices with slow or unreliable connections struggle to handle higher resolution content.

Innovation Solution

A method and system that recommend content based on network conditions by determining user context and network connectivity information, scoring media content items based on viewing metrics, and adaptively streaming content by separating portions for different resolutions, ensuring optimal quality based on the user's connection status.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If media content is streamed with higher resolution, then content quality is improved, but network bandwidth consumption increases and playback reliability deteriorates on slow connections

Engineering Contradiction:

Improvecontent qualityVSAvoidplayback reliability

Core Design Contradiction:

Manufacturing precisionVSReliability

Solution Approach 1:

The system dynamically adjusts the resolution of media content based on real-time network conditions. The server monitors network bandwidth and connection status, then adaptively selects appropriate resolution levels for streaming, allowing the content quality to vary dynamically rather than being fixed, thus maintaining playback reliability while optimizing quality when possible

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes the resolution parameter of media content based on network conditions. By adjusting this key parameter according to available bandwidth and connection stability, the system resolves the contradiction between maintaining high content quality and ensuring reliable playback on varying network connections

Inventive Principle:

Principle #35Parameter changes

2Manufacturing precision

If media content is streamed with higher resolution, then content quality is improved, but bandwidth consumption increases for devices with slow connections

Engineering Contradiction:

Improvecontent qualityVSAvoidbandwidth consumption

Core Design Contradiction:

Manufacturing precisionVSLoss of energy

Solution Approach 1:

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system converts the limitation of slow network connections into a beneficial feature by automatically selecting appropriate lower resolutions that match the available bandwidth. This prevents wasteful bandwidth consumption while still delivering the highest possible quality that each network condition can support, turning the harmful constraint into an optimization opportunity

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

3Ease of operation

If content recommendations are personalized based on user context, then user satisfaction is improved, but system complexity increases

Engineering Contradiction:

Improveuser satisfactionVSAvoidsystem complexity

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The system automatically collects user context information (location, activity, device type) and network conditions, then uses this data to generate personalized content recommendations without requiring manual user input. The system serves itself by autonomously processing context data and making intelligent recommendations, improving user satisfaction while managing complexity through automation rather than manual configuration

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS12137132B2Methods, systems, and media for recommending content based on network conditions

Publication Date: 2024.11.05 GOOGLE LLC

AI summary

In some embodiments, a method for recommending content based on network conditions comprises: receiving, from a first user device, a request to present media content recommendations on the first user device; in response to receiving the request, determining information indicating a user context associated with the first user device and network connectivity information associated with a connection status of the first user device over a communications network; identifying a group of media content items to recommend based on the user context and the network connectivity information; and causing recommendations for the group of media content items to be presented on the first user device.