SYSTEMS AND METHODS FOR GENERATING ALTERNATIVE CONTENT RECOMMENDATIONS

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SYSTEMS AND METHODS FOR GENERATING ALTERNATIVE CONTENT RECOMMENDATIONS - A simplified explanation of the abstract

This abstract first appeared for US patent application 18130896 titled 'SYSTEMS AND METHODS FOR GENERATING ALTERNATIVE CONTENT RECOMMENDATIONS

The abstract describes a computer-implemented method for generating content recommendations based on user data and relationship information.

User data, including user activity and content metadata, is obtained for a selected user.
Relationship information for content metadata is generated or obtained.
Further user data is generated using the relationship information to include alternative content metadata.
A content recommendation process is performed using the further user data and content information to generate recommendation candidates for the user.

Potential Applications: - Personalized content recommendations for users on content distribution platforms. - Enhanced user engagement and satisfaction through tailored content suggestions.

Problems Solved: - Addressing the challenge of providing relevant content recommendations to users. - Improving user experience by offering personalized content suggestions.

Benefits: - Increased user engagement and interaction with the content distribution system. - Enhanced user satisfaction and retention through personalized recommendations.

Commercial Applications: - This technology can be utilized by content distribution platforms to improve user experience and drive user retention. - It can also be integrated into e-commerce platforms to suggest relevant products to customers based on their browsing history.

Questions about the technology: 1. How does the relationship information impact the generation of further user data for content recommendations? 2. What are the key factors considered in the content recommendation process to ensure relevance to the user?

Original Abstract Submitted

A computer-implemented method for obtaining one or more recommendation candidates for items of content available via a content distribution system, the method comprising: obtaining user data for a selected user, wherein the user data comprise or represent user activity and/or content metadata associated with user activity; generating or otherwise obtaining relationship information for at least some content metadata associated with the available content; generating further user data from the user data using the relationship information so that the further user data comprises or represents alternative content metadata that are distinct or at most overlap with the content metadata associated with the user activity; performing a content recommendation process using at least the further user data and content information for the available content to generate one or more content recommendation candidates for the user.