18678385. Behavioral Curation of Media Assets simplified abstract (Apple Inc.)
Contents
Behavioral Curation of Media Assets
Organization Name
Inventor(s)
Sabrine Rekik of San Francisco CA (US)
Marcos Regis Vescovi of Capitola CA (US)
Eric Circlaeys of Los Gatos CA (US)
Behavioral Curation of Media Assets - A simplified explanation of the abstract
This abstract first appeared for US patent application 18678385 titled 'Behavioral Curation of Media Assets
The abstract of the patent application describes a method for creating a semantic mapping of features in a subset of assets in a media library, analyzing assets using the mapping to generate semantic scores, and presenting top-rated assets prominently in a user interface.
- Simplified Explanation:
- The patent application outlines a process for identifying and ranking features in a subset of assets in a media library based on semantic mapping. - The method involves analyzing assets to generate semantic scores and highlighting top-rated assets in a user interface.
- Key Features and Innovation:
- Creation of a semantic mapping for features in a subset of assets. - Analysis of assets using the semantic mapping to generate semantic scores. - Presentation of top-rated assets prominently in a user interface.
- Potential Applications:
- Content recommendation systems. - Media asset management. - User interface design for media libraries.
- Problems Solved:
- Efficiently identifying and ranking assets based on semantic features. - Enhancing user experience by highlighting top-rated assets.
- Benefits:
- Improved content discovery. - Enhanced user engagement. - Streamlined asset management.
- Commercial Applications:
- "Semantic Mapping and Ranking System for Media Libraries": Potential for use in streaming platforms, digital asset management systems, and online media libraries.
- Prior Art:
- Prior research on semantic analysis in media libraries. - Existing methods for content recommendation based on user preferences.
- Frequently Updated Research:
- Ongoing studies on semantic analysis algorithms for media content. - Research on user interaction patterns in media libraries.
Questions about Semantic Mapping and Ranking System for Media Libraries:
1. How does the semantic mapping process improve content discovery for users? - The semantic mapping process enhances content discovery by identifying and ranking assets based on semantic features, leading to more relevant recommendations for users.
2. What are the key benefits of presenting top-rated assets prominently in a user interface? - Presenting top-rated assets prominently in a user interface improves user engagement and streamlines the content discovery process, ultimately enhancing the overall user experience.
Original Abstract Submitted
In some implementations, a computing device may create a semantic mapping that includes identified features that appear in a particular percentage of assets in a subset of assets of a media library. Also, the computing device may analyze assets of the media library using the semantic mapping to generate semantic scores, which may be used to determine a first tier of assets from the media library that rate highest for semantic score out of all assets. The computing device may present at least one of the first tier assets prominently in a user interface when viewing assets of the media library.
