US 2025/0148280 A1 · TECHNIQUES FOR LEARNING CO-ENGAGEMENT AND SEMANTIC RELATIONSHIPS USING GRAPH NEURAL NETWORKS

Abstract

One embodiment of a method for training a machine learning model includes generating a graph based on one or more semantic concepts associated with a plurality of entities and user engagement with the plurality of entities, and performing one or more operations to train an untrained machine learning model based on the graph to generate a trained machine learning model.

Claims20

Dependent claims

A computer-implemented method for training a machine learning model, the method comprising:

generating a graph based on one or more semantic concepts associated with a plurality of entities and user engagement with the plurality of entities;
and
performing one or more operations to train an untrained machine learning model based on the graph to generate a trained machine learning model.

One or more non-transitory computer-readable media storing instructions that, when executed by at least one processor, cause the at least one processor to perform steps comprising:

generating a graph based on one or more semantic concepts associated with a plurality of entities and user engagement with the plurality of entities;
and
performing one or more operations to train an untrained machine learning model based on the graph to generate a trained machine learning model.

Dependencies are inferred from the claim text.

Facts

Application

18/905,006Filed 2 Oct 2024

Priority

6 Nov 2023

Published

8 May 2025

Term ends

Not estimatedThe source records don’t support an estimate.

Classification4 codes

G06N 3/08
Neural networks: learning methods
G06N 3/042
Architecture, e.g. interconnection topology: knowledge-based neural networks; Logical representations of neural networks
G06N 5/022
Knowledge representation; Symbolic representation: knowledge engineering; Knowledge acquisition
G06N
AI and machine learning

Techniques for learning co-engagement and semantic relationships using graph neural networks

Life of this patent

Techniques for learning co-engagement and semantic relationships using graph neural networks

Life of this patent

Abstract

Claims20