Contextual Tag Mapping for Privacy-Safe Supplemental Content Insertion
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Solution Overview
Problem
Existing content delivery systems face challenges in efficiently inserting supplemental content during breaks in main content due to the diminishing ability to match viewer data with supplemental content, exacerbated by regulatory restrictions and platform policies, necessitating a method that does not rely on user-specific data.
Innovation Solution
A contextual matching process that uses a prediction network to map contextual tags from main content to standard tags, allowing for efficient insertion of supplemental content without user account-specific characteristics, utilizing a language encoder and classifier trained on sentiment awareness to determine relevant supplemental content for breaks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If user data and viewer segments are used to match supplemental content, then content relevance and engagement are improved, but regulatory compliance and data privacy are worsened
Solution Approach 1:
The patent introduces contextual tags as an intermediary element that bridges main content and supplemental content without requiring user data. The contextual tags provider generates tags from main content metadata, which then serve as the matching criterion for supplemental content, eliminating the need to directly use viewer personal data while maintaining relevance.
Solution Approach 2:
The patent creates a copy of the matching mechanism that operates on contextual tags instead of user data. The prediction network maps contextual tags to standard tags, providing a parallel matching process that achieves content relevance without the harmful dependency on viewer personal information and explicit consent.
2Measurement precision
If viewer personal data and tracked activity are used for content matching, then targeting accuracy is improved, but data protection and user privacy are worsened
Solution Approach 1:
The patent extracts the matching function from user data and relocates it to contextual tags. The contextual tags provider extracts relevant information from main content metadata and generates tags that can be used for matching without any user data. This extraction separates the matching capability from the problematic data source.
Solution Approach 2:
The patent implements a copy of the matching process that uses contextual tags instead of viewer personal data. The prediction network creates a mapping from contextual tags to standard tags, providing an alternative matching mechanism that maintains targeting accuracy while eliminating dependency on protected data.
3Measurement precision
If contextual tags are mapped through a prediction network, then content relevance is improved, but system complexity is worsened
Solution Approach 1:
The patent performs preliminary action by pre-mapping contextual tags to standard tags through the prediction network during content analysis. This pre-processing allows the system to leverage existing standard tag infrastructure for supplemental content matching, reducing the need for complex real-time matching algorithms and simplifying the overall system architecture.
Data Source
AI summary
In some embodiments, a method determines a prediction network that is trained to map a contextual taxonomy to a standard taxonomy. An indication of a break that is going to be experienced during playback of an instance of main content is received. A client device is playing back the instance of main content. The method determines a set of contextual tags based on content associated with the break in the instance of main content. The prediction network maps the set of contextual tags to a set of standard tags from the standard taxonomy. The method determines an instance of supplemental content based on the set of standard tags. The information to insert the instance of supplemental content in the break during a playback of the instance of main content is provided to the client device.