Cross-Provider Media Recommendations for User Cold Start
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Solution Overview
Problem
Content recommendation engines face challenges in providing personalized recommendations due to the 'user cold start' problem, where little is known about new subscribers, and they often function in isolation, leading to frustration and inefficiencies in content delivery.
Innovation Solution
A content recommendation engine that shares user interaction histories across multiple providers, allowing for profile creation and content item recommendations based on user preferences and availability, even when content is unavailable from the primary provider.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a content recommendation engine functions in isolation to protect user privacy and maintain system independence, then system security and autonomy are improved, but the ability to provide personalized recommendations for new users deteriorates due to the cold start problem
Solution Approach 1:
The patent introduces a shared user registry as an intermediary system that stores user profile information and interaction histories. This registry acts as a mediator between content providers, allowing them to access user data without directly sharing information between systems. The registry enables new content providers to retrieve existing user profiles and provide personalized recommendations from day one, while maintaining system independence and security through centralized managed access.
2Measurement precision
If user profile information is manually programmed for each household member, then personalized recommendations can be provided, but the complexity and time required for setup increases significantly
Solution Approach 1:
The patent implements preliminary action by automatically creating user profiles and populating them with interaction histories before users even begin using the service. When a new user subscribes, the system proactively retrieves their existing profile data from the shared registry and pre-configures personalized recommendations. This eliminates the need for manual profile programming and setup complexity, while delivering accurate personalized recommendations immediately.
3Measurement precision
If the recommendation engine recommends content that is unavailable from the content library or content schedule, then user preferences are accurately reflected, but user frustration increases due to inability to access recommended content
Solution Approach 1:
The patent implements multi-functionality by enabling the recommendation engine to search across multiple content providers' libraries and schedules simultaneously. When content is unavailable from the primary provider, the system automatically queries partner content providers through the shared registry to find alternative sources. This allows the system to maintain accurate preference matching while ensuring content accessibility by recommending available content from any connected provider.
Data Source
AI summary
Media content recommendations and user profile display recommendations, including user names and icons of users associated with the subscription, may be provided, for example, upon cold start of a user subscription. A content provider may request a history of user interactions and profile information from a second content provider and then determine that the content items were not previously consumed by this user, and transmit content recommendations accordingly. Generating for play content items not available from a first content provider but available from a second content provider is also contemplated. The content item may be transmitted to the user device via an application associated with the first content provider on the user device, or via an application associated with the second content provider on the user device.