Media Content Classification System Using Author-Based Criteria
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Solution Overview
Problem
Conventional media content discovery systems struggle to effectively showcase and promote content from unknown or small content providers due to their reliance on brand recognition, leading to difficulties in user discovery of relevant media items amidst a vast number of options.
Innovation Solution
A computer-based media content classification and discovery system that utilizes a database to store content representative identifiers keyed to author-based, content-centered criteria elements, allowing users to filter and search media items through a graphical user interface with selectable fields matching these criteria, enabling more precise content discovery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If content is grouped by genre in conventional systems, then users can retrieve content slightly more related to their desires, but the sorting remains vague and insufficient when there are thousands-to-millions of titles
Solution Approach 1:
The patent segments content classification into multiple hierarchical levels (broad genres to specific sub-genres) and dimensions (genre, mood, format, etc.), allowing users to navigate from general to specific classifications. This segmentation enables precise content identification without requiring a single complex classification system, as users can drill down through multiple manageable classification layers.
Solution Approach 2:
The patent introduces multiple classification dimensions beyond traditional genre (including mood, format, target audience, and other metadata) to create a multi-dimensional classification space. This allows content to be organized and retrieved along different axes, providing precise filtering capabilities without increasing the complexity of any single classification dimension.
2Reliability
If conventional systems rely on brand recognition for content marketing, then well-known content providers can achieve visibility, but unknown or small content providers face insurmountable problems having their submissions discovered
Solution Approach 1:
The patent enables content to serve itself by allowing authors to tag and categorize their own work with relevant metadata and classification elements. This self-service classification approach ensures that content from unknown providers is properly categorized without requiring brand recognition, making discovery reliable and easy for all content providers regardless of their market position.
3Quantity of substance
If the number of content items increases to thousands-to-millions of titles, then market volume increases, but users face frustration in identifying good apps among the vast options
Solution Approach 1:
The patent applies preliminary classification and tagging to all content items during ingestion, organizing them into structured classification frameworks before users need to search. This preliminary action creates ready-to-filter datasets that enable users to quickly identify relevant content among millions of items through pre-organized classification structures and metadata.
Data Source
AI summary
A computer-based media content classification and discovery system includes a computerized database storing content representative identifiers corresponding to content items. Each of the content representative identifiers is keyed to a plurality of author-based, content-centered criteria elements, which are identified by an author of the each of the content items. A plurality of user computer devices is in communication with the computerized database. At least one input selection field is displayed on a GUI of the user computer devices. The input selection field has a plurality of selectable fields which matches at least one of the plurality of author-based, content-centered criteria elements. A result of the filtered selectable fields is displayed on the GUI. The result has a portion of the plurality of content items keyed to the plurality of author-based, content-centered criteria elements.