Twilio inc. (20240330765). EFFICIENT FEATURE MERGING AND AGGREGATION FOR PREDICTIVE TRAITS simplified abstract

EFFICIENT FEATURE MERGING AND AGGREGATION FOR PREDICTIVE TRAITS

Organization Name

twilio inc.

Inventor(s)

Carlos Alberto Oliveira of San Diego CA (US)

Alfredo Lainez Rodrigo of Madrid (ES)

Rowan Michael Wing of Longmont CO (US)

Maria del Pilar Fernandez Gallego of Madrid (ES)

Sebastian Montes of Madrid (ES)

Akshay Chandrashekaran of Boston MA (US)

Ankit Awasthi of San Francisco CA (US)

EFFICIENT FEATURE MERGING AND AGGREGATION FOR PREDICTIVE TRAITS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240330765 titled 'EFFICIENT FEATURE MERGING AND AGGREGATION FOR PREDICTIVE TRAITS

The patent application describes a system and method for accessing a feature associated with multiple user identities, mapping these identities to canonical user IDs, generating groups of feature values based on these mappings, aggregating these values to calculate aggregate feature values, computing predictive traits for the canonical user IDs, and displaying these traits on a user interface.

• Accessing a feature linked to various user identities
• Mapping user identities to canonical user IDs
• Generating feature values based on these mappings
• Aggregating feature values to calculate aggregate values
• Computing predictive traits for canonical user IDs
• Displaying computed predictive traits on a user interface

Potential Applications: - Personalized recommendations in e-commerce platforms - Targeted advertising based on user traits - Fraud detection in financial transactions - Customized content delivery in media streaming services

Problems Solved: - Efficiently analyzing and predicting user behavior across multiple identities - Streamlining data processing for personalized services - Enhancing user experience through tailored recommendations

Benefits: - Improved user engagement and satisfaction - Enhanced data-driven decision-making for businesses - Increased efficiency in delivering personalized services

Commercial Applications: Title: "Enhanced User Profiling System for Personalized Services" This technology can be utilized in various industries such as e-commerce, advertising, finance, and media to enhance user experiences and drive business growth through targeted services and recommendations.

Questions about the technology: 1. How does this system ensure data privacy and security for user identities? 2. What measures are in place to prevent bias in the computation of predictive traits?

Original Abstract Submitted

system and method including accessing a feature associated with a plurality of user identities (ids); accessing a structure specifying mappings between the plurality of user ids and a plurality of user canonical ids; generating groups of feature values of the feature based on the mappings, each group of feature values being associated with a corresponding group of user ids and with a corresponding user canonical id; aggregating each group of feature values to calculate an aggregate feature value of the feature, each aggregate feature value associated with the corresponding user canonical id; computing predictive traits associated with the plurality of user canonical ids, the predictive traits including likelihoods of events or trait values, the computation of the predictive traits using the aggregate feature values associated with the corresponding user canonical ids; and causing display, at a user interface (ui) of a computing device, of the computed predictive traits.