US 2026/0289394 A1 · Reward-Based Training of an Interest-Generating Model for use in Retrieving Items

Abstract

A technique trains an interest-generating model that maps activity data to a set of candidate interest key phrases. The activity data describes prior action in interacting with computer-implemented services. Once trained, the interest-generating model is used to select and serve items. The technique for training reduces noise in its output results by first filtering the activity data using a filtering model, to produce filtered activity data. The technique then trains the interest-generating model to produce key phrases that are effective in both (1) expressing the interests underlying the filtered activity data and (2) retrieving items from a retrieval engine that are likely to consumed when served, given the identified interests. The technique accomplishes the above goals using reward-based training, which involves scoring candidate interest key phrases based on their effectiveness in retrieving relevant items, and fine-tuning the interest-generating model based on the scored candidate interest key phrases.

Claims20

Dependent claims

A method for training an interest-generating model, comprising:

receiving initial activity data from one or more data stores that describes interactions with one or more computer-implemented services;
filtering the initial activity data using a machine-trained filtering model to remove a subset of the initial activity data that represents noise, to produce filtered activity data;
mapping the filtered activity data to a set of candidate interest key phrases;
assigning scores to the candidate interest key phrases using a machine-trained reward system, to produce scored candidate interest key phrases, each score assigned to a particular candidate interest key phrase describing an effectiveness of the particular candidate interest key phrase in retrieving items from a retrieval engine that will be selected when served;
and
performing reward-based training of the interest-generated model based on the scored candidate interest key phrases,
upon completion of the reward-based training, the interest-generating model aligning an information space associated with the filtered activity data with an information space associated with an index of the retrieval engine and associated consumption metrics that describe prior consumption of available items in the index.

4 more elements

A computing system for retrieving items, comprising:

an instruction data store for storing computer-readable instructions;
and
a processing system for executing the computer-readable instructions in the data store, to perform operations including:
receiving user activity data that describes activity performed by a particular user in interacting with one or more computer-implemented services;
removing noise from the user activity data, to produce filtered user activity data;
mapping the filtered user activity data to a set of one or more user interest key phrases using an interest-generating model;
retrieving a set of one or more items from a retrieval engine based on the set of one or more user interest key phrases;
and
generating output information that identifies the set of one or more items,
wherein the interest-generating model has been trained using reward-based training that aligns an information space associated with the filtered user activity data with an information space associated with an index of the retrieval engine and associated consumption metrics that describe prior consumption of available items in the index.

7 more elements

Dependencies are inferred from the claim text.

Reward-Based Training of an Interest-Generating Model for use in Retrieving Items

Life of this patent

Reward-Based Training of an Interest-Generating Model for use in Retrieving Items

Life of this patent

Abstract

Claims20