Media Content Source Ranking via Annotation Scoring
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Solution Overview
Problem
Users face difficulty in finding and subscribing to media content sources that interest them due to the vast quantity of available online media content sources, such as video channels, social network profiles, and data feeds.
Innovation Solution
A processing device identifies media items that meet specific criteria, determines annotations and scores for media content sources based on the quantity of annotations, descriptions, and comments referencing them, and ranks these sources for presentation to users, facilitating easier discovery and subscription.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users browse through all available media content sources, then they can find sources that interest them, but the time and effort required increases significantly
Solution Approach 1:
The patent replaces manual browsing and user effort with an automated scoring system that calculates relevance scores based on annotations, descriptions, and comments. This automated mechanism substitutes the mechanical process of user searching with an intelligent ranking system that automatically identifies and prioritizes relevant media content sources.
Solution Approach 2:
The patent transforms the vast quantity of media content sources into a manageable ranked list by changing the parameter of presentation from raw quantity to scored relevance. By calculating and applying relevance scores based on multiple factors (annotations, descriptions, comments), the system reorders and prioritizes content sources, making them easier to navigate and select.
2Loss of information
If the system provides all media content sources to users, then users have complete information, but the complexity of the system increases
Solution Approach 1:
The patent extracts only the most relevant media content sources from the complete set by applying relevance scoring and filtering. Instead of presenting all available sources, the system extracts and prioritizes those with highest relevance scores, reducing information overload while maintaining the essential complete information needed for user decision-making.
Solution Approach 2:
The patent segments the vast media content source database into manageable ranked groups based on relevance scores. By dividing the complete set into prioritized segments (highest to lowest relevance), the system makes the information more digestible and easier to navigate without losing access to the complete underlying data set.
3Measurement precision
If the system analyzes all annotations, descriptions, and comments to rank media content sources, then the ranking accuracy improves, but the processing time and computational resources increase
Solution Approach 1:
The patent applies partial action by focusing analysis on the most significant factors (annotations, descriptions, comments) rather than attempting to analyze every possible attribute of media content sources. This selective analysis approach achieves sufficient ranking accuracy without requiring exhaustive processing of all available data, thereby maintaining reasonable processing speeds.
Data Source
AI summary
A processing device identifies a plurality of media items that have been accessed by a user. The processing device determines a plurality of annotations in the plurality of media items that identify a plurality of media content sources. The processing device calculates scores for the plurality of media content sources, wherein a score for a media content source of the plurality of media content sources is calculated based at least in part on a quantity of the plurality of annotations that identify the media content source. The processing device ranks the plurality of media content sources based on the calculated scores. The processing device the provides one or more ranked media content sources for presentation to the user.