How Computers Automatically Tag Movies and Shows Better

This patent describes a system for automatically improving how movies, TV shows, and other media are tagged with descriptive labels by comparing them to similar content using a special ratio.

What it covers

This system helps a computing device automatically assign or update descriptive labels, called metadata tags, for content items like movies or songs. It works by first finding other content items that are similar to the one being tagged. Then, it calculates a ratio: it compares how similar the first content item is to *all* its similar items against how similar it is to only those similar items that *already have the specific tag* in question (Claim 1). If this ratio indicates a strong connection, the system modifies the content item's metadata field to include that tag. For example, if a new documentary is very similar to many other documentaries already tagged as 'historical,' the system might automatically add 'historical' to the new documentary's tags.

What it doesn't cover

• —Does not cover manual tagging of content by human editors without automated similarity analysis.
• —Does not cover content recommendation systems that do not rely on this specific ratio-based metadata modification process.
• —Does not cover the underlying methods for determining content similarity itself, only how to use that similarity for metadata modification.
• —Does not cover systems that only add tags based on simple keyword matching without comparing to other content items.
• —Does not cover systems that only remove metadata tags without considering a history of such removals for recommendations.

The clever bit

The novelty lies in using a specific ratio of aggregate similarities to determine if a metadata tag is truly applicable. Instead of just checking if an item is similar to *some* tagged items, it compares overall similarity against similarity to *only* the similar items with that specific tag, providing a more precise applicability score.

Why it matters

Accurate content classification is crucial for modern streaming services and digital media platforms. This patent provides a method to automatically refine these classifications, which directly impacts how effectively content can be discovered and recommended to users. Better tagging leads to more relevant recommendations, improving user experience and engagement across various media platforms.

Real-world examples

• 1.Netflix content classification
• 2.Hulu content categorization
• 3.Amazon Prime Video recommendations
• 4.YouTube video tagging
• 5.Spotify music genre assignment