/Personalized Recommendation Systems To Remediate Inefficiencies In User Behavior
Abstract

A method for generating predictive and event-based action recommendations includes receiving, from at least one data source, input data representative of a user; generating, using a first machine learning model, a user behavior pattern for the user based on the input data representative of the user; classifying the user behavior pattern based on one or more personas representative of user characteristics; identifying, based on at least the input data and the one or more personas, an inefficiency in the user behavior pattern impacting a goal of the user; and generating, using a second machine learning model, a personalized recommendation for the user to remediate the inefficiency.

Full Text

What is claimed is:

A method for generating predictive and event-based action recommendations includes receiving, from at least one data source, input data representative of a user; generating, using a first machine learning model, a user behavior pattern for the user based on the input data representative of the user; classifying the user behavior pattern based on one or more personas representative of user characteristics; identifying, based on at least the input data and the one or more personas, an inefficiency in the user behavior pattern impacting a goal of the user; and generating, using a second machine learning model, a personalized recommendation for the user to remediate the inefficiency.
Timeline
Filed
06/15/2026
Published
10/01/2026
Granted
Not Available
IPC Codes(5)
G06Q 30/0207:Discounts or incentives, e.g. coupons or rebates
G06N 5/022:Knowledge engineering; Knowledge acquisition
G06Q 10/1057:Benefits or employee welfare, e.g. insurance, holiday or retirement packages