Self-Organizing Map for N-Dimensional Media Content Organization
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Solution Overview
Problem
Conventional television program guides provide insufficient information for viewers to decide on program interest, as they typically display short, generic descriptions in a single dimension, lacking the depth needed for informed selection.
Innovation Solution
A self-organizing map is applied to television media content metadata, organizing it into n-dimensional arrays based on various attributes, allowing for dynamic traversal and display on user interfaces to facilitate viewer selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional program guides display short, generic descriptions in a single dimension, then the device complexity is low, but the information completeness is insufficient for viewers to make informed decisions
Solution Approach 1:
The patent applies a self-organizing map to transform the program guide from a single-dimensional linear display into an n-dimensional spatial structure. Programs are positioned in multi-dimensional space based on multiple attributes simultaneously (genre, rating, time, etc.), allowing viewers to navigate and filter content along different dimensional axes. This dimensional expansion preserves all program information attributes while organizing them in a comprehensible spatial framework that resolves the contradiction between information completeness and structural complexity.
2Loss of information
If program guides provide detailed program descriptions and multiple attributes, then the information completeness improves, but the ease of operation deteriorates due to increased complexity
Solution Approach 1:
By organizing programs in n-dimensional space where each dimension corresponds to a specific attribute (genre, rating, time slot, etc.), the system allows users to navigate by moving along specific dimensional axes rather than scrolling through linear lists. This spatial organization enables intuitive filtering and searching by simply adjusting position along relevant dimensions, making detailed information accessible without increasing operational complexity.
Solution Approach 2:
The self-organizing map creates local clusters of programs with similar attributes in specific regions of the n-dimensional space. Users can focus on local areas of interest (e.g., high-rated comedy programs in a specific time slot) without being overwhelmed by the entire program database. This local organization allows detailed information to be presented in contextually relevant groups, improving ease of operation while maintaining information completeness.
Data Source
AI summary
Self-organizing media content is described. In embodiment(s), a self-organizing map can be applied to metadata that corresponds to television media content. A media content array of television media content choices can then be generated based on the mapped metadata where the media content array is organized to include n-dimensions that are each based on a different attribute of the metadata. The media content array can then be displayed on a user interface that facilitates dynamic traversal of the media content array for viewer selection of the television media content choices.