Context-Relevant Supplemental Content Selection
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Solution Overview
Problem
Existing media delivery systems fail to provide context-relevant supplemental content to users, making it uninteresting and unvaluable, as it is not tailored to the specific media content, user preferences, or consumption context.
Innovation Solution
A system and method that determine context information of media content and select relevant supplemental content based on this information, integrating it with the media stream for presentation to users, using a context detection and supplemental content selection system that can receive non-media context information and transmit the selected content through various channels to destination devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If supplemental content is provided to users, then content providers can generate income and users can receive additional information, but the supplemental content is not relevant to the context of the particular user consuming the particular media content
Solution Approach 1:
The system performs preliminary actions by determining context information about the user and media content before selecting supplemental content. This advance analysis of user preferences, media characteristics, and consumption context enables the selection of highly relevant supplemental content, resolving the contradiction between providing general supplemental content and delivering context-relevant content.
Solution Approach 2:
The system applies local quality by tailoring supplemental content selection to specific local contexts rather than applying a uniform approach. By analyzing individual user preferences, specific media content characteristics, and consumption context, the system delivers customized supplemental content that is locally optimized for each user-media context, thereby improving relevance and adaptability simultaneously.
2Ease of operation
If context information is determined and used to select supplemental content, then user interest and engagement increase, but system complexity increases
Solution Approach 1:
The system introduces an intermediary context detection and supplemental content selection system that bridges the gap between media content delivery and user preferences. This intermediary layer analyzes context information and makes intelligent selections, shielding users from the complexity of the selection process while delivering highly relevant content, thus improving ease of operation without exposing users to system complexity.
Solution Approach 2:
The system implements self-service by automatically determining context information and selecting supplemental content without requiring user intervention. The system autonomously analyzes user preferences, media characteristics, and consumption context to make selections, reducing the operational burden on users while maintaining high relevance, thereby improving ease of operation without requiring users to manage system complexity.
Data Source
AI summary
Media content is paired with context-relevant supplemental content, and the media and supplemental content are provided to a user. A media stream containing the media content may be received from a source system, and context information about the media content is determined from information about the media stream. The supplemental content may be selected based on the determined context information. This may enable a business model in which third parties can register advertising or other supplemental content and specify the criteria that cause it to be combined with the media content.