Patent ID: 11934472
Assignee: YAHOO ASSETS LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method, comprising:
monitoring user activity, of a plurality of users, across a plurality of internet resources;
identifying, in the user activity, a first plurality of content events;
generating, based upon the first plurality of content events, a plurality of user profiles associated with the plurality of users, wherein each user profile is indicative of an entity in which a user, of the plurality of users, has an interest;
extracting first entities from the plurality of user profiles;
retrieving, from one or more first remote devices, supplemental information for each of the first entities;
generating first vector representations of the first entities using the supplemental information for each of the first entities, wherein each of the first vector representations is generated based upon supplemental information associated with a corresponding entity of the first entities;
evaluating a second plurality of content events to identify a plurality of content items;
extracting second entities from content information associated with the plurality of content items;
retrieving, from one or more second remote devices, supplemental information for each of the second entities;
generating second vector representations of the second entities using the supplemental information for each of the second entities, wherein each of the second vector representations is generated based upon supplemental information associated with a corresponding entity of the second entities;
determining, based upon at least one of the plurality of user profiles or the second plurality of content events, a plurality of user-associated metrics associated with the first entities, wherein:
a first user-associated metric is representative of online activity of one or more first users having an interest in a first entity of the first entities; and
a second user-associated metric is representative of online activity of one or more second users having an interest in a second entity of the first entities;

processing, using a neural network model, the first vector representations and the second vector representations to generate an attention distribution array, wherein each value of the attention distribution array represents, for a user interested in an entity of the first entities, a proportion of (i) entity-specific activity, of the user, related to an entity of the second entities relative to (ii) an entirety of activity of the user;
generating an inferred activity distribution array by applying the plurality of user-associated metrics to the attention distribution array;
generating a filtered subset of activity distribution values by pruning values from the inferred activity distribution array;
training a profile-processing machine learning model using the filtered subset of activity distribution values to generate a trained profile-processing machine learning model; and
controlling transmission of content using the trained profile-processing machine learning model.