Digital Content Classification via Poster Frames and Keyword Panes
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Solution Overview
Problem
Current digital content classification methods are inefficient for organizing and editing large collections of video, audio, and image files, as they lack a structured approach to categorize and sort content based on quality and context, making it difficult for users to quickly access and edit relevant items.
Innovation Solution
A computer-implemented method and system that displays digital content as poster frames in a user interface, allowing users to classify items using first and second-level classification panes associated with keywords, enabling grouping and editing of content based on metadata, with automatic generation of keywords for improved organization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually organize and classify large collections of digital content, then content can be categorized and sorted, but the process becomes time-consuming and inefficient
Solution Approach 1:
The system automatically generates keywords and classifies content without requiring manual user input. The computer-implemented method extracts meaningful terms from content metadata and performs classification autonomously, allowing the system to serve itself rather than requiring continuous user intervention for organization tasks.
Solution Approach 2:
The system performs preliminary classification by generating keywords and organizing content into categories before the user needs to access or edit the content. This advance organization ensures that when users do need to work with the content, it is already sorted and ready for efficient retrieval and editing.
2Ease of operation
If a simple classification system is used, then the interface remains easy to use, but it lacks the structured approach needed for organizing large content collections
Solution Approach 1:
The classification system is divided into multiple levels, with first-level categories providing broad organization and second-level categories offering more specific classification. This segmented approach allows the interface to remain simple while providing the structured versatility needed for organizing large content collections, as users can work at whichever level is most appropriate for their current task.
Solution Approach 2:
The system adds a temporal dimension to classification by automatically generating keywords and organizing content based on metadata analysis. This creates an additional organizational layer beyond traditional manual categorization, enabling the system to handle complex content collections while maintaining interface simplicity through automated intelligence.
3Measurement precision
If multiple classification levels are implemented, then content organization becomes more detailed and accurate, but the system complexity increases
Solution Approach 1:
The classification system is designed to be dynamic rather than static. The computer-implemented method automatically generates keywords and adjusts classifications based on content analysis, allowing the system to adapt to different content types and user needs. This dynamic approach maintains high classification accuracy while managing system complexity through intelligent automation rather than rigid multi-level structures.
4Productivity
If automatic keyword generation is used, then content classification is improved, but reliance on metadata accuracy is increased
Solution Approach 1:
The system incorporates feedback mechanisms where classification results can be reviewed and adjusted. The computer-implemented method generates keywords and classifications automatically, but the multi-level classification structure allows users to provide feedback by adjusting categories or adding corrections, which then refines future automatic classification accuracy while maintaining high productivity.
Data Source
AI summary
A computer-implemented method for classifying digital content can include displaying one or more poster frames in a user interface, wherein a poster frame corresponds to an item of digital content, displaying one or more first level classification panes adjacent to a poster frame corresponding to an item to be classified, wherein a first level classification pane is associated with a keyword, and enabling a user to associate a poster frame with a first level classification pane to cause the keyword associated with the first level classification pane to be associated with the item to which the poster frame corresponds.