REAL-TIME CONTENT INTEGRATION BASED ON MACHINE LEARNED SELECTIONS

Organization Name

Inventor(s)

Rodrigo B. Farnham of Los Angeles CA (US)

Nicholas J. Stucky-mack of Los Angeles CA (US)

REAL-TIME CONTENT INTEGRATION BASED ON MACHINE LEARNED SELECTIONS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240275845 titled 'REAL-TIME CONTENT INTEGRATION BASED ON MACHINE LEARNED SELECTIONS

The abstract of the patent application describes a method for selecting and integrating content items based on bid value and relevancy value to present aggregated content on a user's device.

Content request received from user's device
Identification of candidate content items with bid values
Automatic generation of relevancy value for each candidate content item
Calculation of combined value by adjusting bid value with relevancy value
Automatic selection of candidate content items based on combined value
Integration of selected content items into placeholder areas among pre-selected content items
Presentation of aggregated content on user's device

Potential Applications: - Personalized content recommendation systems - Targeted advertising platforms - Content curation tools for online platforms

Problems Solved: - Efficient selection and integration of relevant content items - Improved user engagement with presented content - Optimization of content delivery based on user preferences

Benefits: - Enhanced user experience through personalized content - Increased engagement and interaction with presented content - Efficient utilization of advertising space on digital platforms

Commercial Applications: Title: "Enhanced Content Selection and Integration Technology for Personalized User Experience" This technology can be utilized in digital advertising platforms, content recommendation systems, and online media outlets to improve user engagement and optimize content delivery based on user preferences.

Questions about the technology: 1. How does the system determine the relevancy value for each candidate content item? 2. What factors are considered in the calculation of the combined value for selecting content items?

Original Abstract Submitted

a content request is received from a device of a user. a plurality of candidate content items is identified. each candidate content item has a bid value. a relevancy value is automatically generated for each candidate content item. the relevancy value indicates whether the candidate content item is likely to be skipped by the user. for each candidate content item, a combined value is automatically generated by adjusting the bid value using the relevancy value generated for the candidate content item. one or more candidate content items are automatically selected based on the combined value generated for each of the one or more candidate content items. the one or more selected candidate content items are automatically integrated into at least one placeholder area among one or more pre-selected content items as part of the aggregated content. the aggregated content is presented on the device of the user.