Content Categorization Manager for Dynamic Video Storefront Curation
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Solution Overview
Problem
Traditional cable television systems and video content delivery services face challenges in dynamically categorizing and updating video content on electronic video storefronts, often requiring manual intervention which is time-consuming and limits the number of categories that can be curated.
Innovation Solution
The Content Categorization Manager (CCM) system allows operators to create criteria for categories, automatically sorting video content based on metadata, thereby eliminating the need for manual assignment and enabling dynamic updates to the storefront.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual intervention is used to categorize and update video content on electronic video storefronts, then content categorization can be performed, but the process is time-consuming and limits the number of categories that can be curated
Solution Approach 1:
The system enables self-service categorization by automatically assigning video content to categories based on metadata criteria without requiring manual intervention. The automated categorization system processes content and updates storefronts independently, eliminating the need for manual content review and classification by operators.
Solution Approach 2:
The patent replaces manual mechanical processes with automated electronic systems. Instead of operators manually reviewing and categorizing content, the system uses automated algorithms that process metadata and automatically assign categories, substituting human labor with electronic automation to improve efficiency and reduce time consumption.
2Adaptability or versatility
If manual assignment of content to categories is performed, then categorization accuracy can be controlled, but the number of categories that can be curated is limited
Solution Approach 1:
The automated categorization system serves multiple functions simultaneously: it processes content from various sources, applies multiple categorization criteria, updates existing categories, and creates new categories as needed. This multi-functional approach allows the system to handle diverse content types and category requirements without requiring separate manual processes for each category.
Solution Approach 2:
The system dynamically adapts to different categorization needs by automatically creating new categories when content requires them and updating existing categories based on changing metadata criteria. This dynamic capability allows the system to respond to evolving content requirements without manual intervention, increasing the number of curatable categories.
3Extent of automation
If automated sorting of video content based on metadata is implemented, then manual assignment is eliminated, but system complexity increases
Solution Approach 1:
The system introduces metadata as an intermediary between content and categories. Instead of directly complex decision-making, the system uses metadata fields as intermediaries that automatically determine category assignments. This intermediary approach simplifies the automation logic by relying on structured data fields rather than complex algorithmic decision trees.
Solution Approach 2:
The automated system works by changing parameters such as metadata fields, content attributes, and categorization criteria to automatically sort and assign content. By manipulating these parameters programmatically, the system achieves high automation levels without requiring overly complex system architecture, as parameter changes are straightforward and efficient.
Data Source
AI summary
The described system allows for dynamic curating of video storefront categories and content using a novel Content Categorization Manager (“CCM”) which among other things, allows an operator to create criteria for a category that defines what content should and should not be associated to a Criteria Based Category (“CBC”). The CCM will periodically use the criteria to calculate what content should be associated to the Target Category. Once this calculation is complete, the category definition and relevant associations will be pushed out to the storefront in accordance with the rules of that storefront.