Content Channel Generation Using Seed References
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Solution Overview
Problem
Current media systems, such as broadcast television and online platforms, fail to consistently and predictably provide channels dedicated to specific types of content, leading to user inefficiency in finding desired content amidst vast and fragmented content libraries.
Innovation Solution
A method for generating content channels that utilize seed references to select content assets based on similarity, allowing for automatic choice and presentation of content to users across multiple services and providers, using user interfaces and network interfaces for playback and settings management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users access vast content libraries across multiple services, then content variety is improved, but time to find desired content increases
Solution Approach 1:
The system performs preliminary actions by pre-selecting and pre-organizing content into channels before the user needs to access it. Content is automatically curated based on user preferences and referenced content, creating ready-to-consume channels that eliminate the need for users to search through vast libraries manually.
Solution Approach 2:
The invention introduces content channels as an intermediary layer between the user and the vast content library. These channels act as mediators that pre-filter and organize content from multiple services, presenting a manageable subset of relevant content rather than requiring users to navigate the entire library.
2Ease of operation
If manual content selection is used, then user control is improved, but productivity decreases
Solution Approach 1:
The system provides self-service by automatically selecting and curating content based on user preferences and referenced content. The content channel system serves itself by using algorithms to determine which content should be included, reducing the need for manual user intervention while maintaining relevance to user interests.
Solution Approach 2:
The content channels are dynamic rather than static, automatically adapting to user preferences and updating content selections based on referenced content. This dynamic behavior allows the system to maintain high productivity by continuously optimizing content selection without requiring manual reconfiguration.
3Adaptability or versatility
If content channels are manually created, then customization is improved, but device complexity increases
Solution Approach 1:
The system uses copying by referencing existing content channels and their characteristics to create new channels. Instead of requiring users to manually configure complex parameters, the system copies the structure and content selection logic from referenced channels, simplifying the customization process while maintaining adaptability.
Solution Approach 2:
The invention simplifies customization by changing parameters at a higher level - rather than requiring users to configure individual content selection parameters, the system allows users to reference existing channels and modify high-level characteristics such as which referenced content to include, reducing the complexity burden.
Data Source
AI summary
An apparatus and method for creating channels dedicated to a particular type of content. The method includes acquiring seed content and using the seed content in the creation or updating of a content list. Additional content for the channel is acquired based on the common features of the content list.