Content Bid Requests With AI Recommendations for User Anonymity
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Solution Overview
Problem
The challenge in content item bidding systems is the difficulty in determining relevant third-party content items without sharing user information, leading to lower engagement and user satisfaction due to the presentation of irrelevant content.
Innovation Solution
A content management system uses a trained AI system with two independent components to generate content item recommendations based on user history and contextual information, allowing third parties to bid on relevant items without knowing user details, while preserving user anonymity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If user information is not shared with third parties, then user anonymity is preserved, but the ability to determine relevant content items deteriorates
Solution Approach 1:
The patent introduces an intermediary system that receives bid requests from third parties, generates content item recommendations using user history and contextual information without sharing personal user data, and returns these recommendations to third parties. This intermediary acts as a mediator that enables relevant content delivery while preserving user anonymity by decoupling the content recommendation process from direct user information access.
2Device complexity
If third parties bid without content item recommendations, then system complexity is reduced, but user engagement deteriorates due to irrelevant content
Solution Approach 1:
The system performs preliminary actions by generating content item recommendations in advance of the bidding process. The bid request processing system analyzes user history and contextual information beforehand to identify relevant content items, then includes these recommendations in the bid response. This preliminary content preparation enables third parties to make more informed bidding decisions and deliver relevant content without requiring them to build complex user analysis capabilities.
3Measurement precision
If content item recommendations are generated using AI systems, then content relevance improves, but processing time increases
Solution Approach 1:
The patent segments the bid request processing into distinct functional components: receiving the bid request, generating content item recommendations using AI analysis of user history and contextual information, and returning the recommendations to the third party. This segmentation allows the system to optimize each component independently, potentially using caching for frequently accessed user history data and parallel processing for AI analysis, thereby reducing overall processing time while maintaining high content relevance.
Data Source
AI summary
Described are systems and methods to determine a content item recommendation that is included in a content item bid request, recommending to a third party, a third party content item to include in a content item bid that is responsive to the bid request. The content item recommendation may indicate a particular third party product or third party content item that is predicted to perform well in a content item slot and for a specific user without disclosing user information to the third party.