Media Content Personalization via Data Chunk Assembly
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing media content delivery systems cannot provide personalized versions of media programs to users based on their individual preferences, leading to a lack of engagement as the content is fixed and statically defined by providers.
Innovation Solution
A media content personalization computing system that receives data chunks of a media content program and generates personalized versions based on user-specific personalization factors, such as interaction profiles, user profiles, hardware profiles, and business rules, allowing for dynamic and tailored content presentation during live transmissions or on-demand playback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed and statically defined media content program is delivered to users, then the content delivery system is simple and reliable, but user engagement and personalization are reduced
Solution Approach 1:
The media content program is divided into multiple data chunks that can be selectively assembled. The system segments the content into discrete units (scenes, segments, or portions) that can be independently managed and reconfigured based on user profiles and preferences, enabling personalization without requiring complete system redesign
Solution Approach 2:
The system transitions from static content delivery to dynamic content assembly. A personalization computing system dynamically selects and assembles data chunks based on real-time user profiles, interaction histories, and preferences, allowing the same base content to be delivered in different configurations to different users
2Adaptability or versatility
If personalized versions of media content are generated for each user, then user engagement increases, but the complexity of content generation and delivery increases
Solution Approach 1:
Instead of creating entirely new content for each user, the system uses copying and reassembly of existing data chunks. Multiple users receive different versions of the same base content by selectively copying and assembling the same pool of data chunks according to individual user profiles, reducing the need for original content creation for each user
Solution Approach 2:
The personalization computing system serves multiple functions: it manages user profiles, selects data chunks, assembles content versions, and delivers personalized media. This multi-functional approach consolidates complexity into a single system that handles all personalization tasks rather than requiring separate systems for each function
3Speed
If data chunks are received and processed in real-time during live transmission, then personalized content can be delivered during the event, but processing time and computational resources increase
Solution Approach 1:
The system receives and buffers data chunks in advance during the media transmission, preparing and pre-assembling personalized versions before the user needs to view the content. This preliminary processing allows the system to maintain real-time delivery speed while performing computational tasks that would otherwise delay content availability
Solution Approach 2:
The personalization computing system operates continuously during media transmission, constantly receiving data chunks, updating user profiles, and pre-assembling personalized versions. This continuous operation ensures that when a user requests personalized content, it is already ready for immediate delivery without interrupting the live transmission or requiring significant processing delays
Data Source
AI summary
An exemplary method includes receiving a plurality of data chunks each representative of a distinct portion of a media content program, generating a personalized version of the media content program based on at least a subset of the data chunks and in accordance with one or more of a plurality of personalization factors associated with a user, and providing the personalized version of the media content program for presentation to the user. Corresponding methods and systems are also described.