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

Claim 17:
18. A non-transitory machine readable medium having stored thereon processor-executable instructions that when executed cause performance of operations, the operations comprising:
extracting first entities from a plurality of user profiles associated with a plurality of users, wherein each user profile is indicative of an entity in which a user, of the plurality of users, has an interest;
generating first vector representations of the first entities;
evaluating a plurality of content events to identify a plurality of content items;
extracting second entities from content information associated with the plurality of content items;
generating second vector representations of the second entities;
determining, based upon the plurality of content events, a plurality of content-associated metrics associated with the second entities, wherein:
a first content-associated metric is representative of online activity performed in association with one or more first content items, of the plurality of content items, associated with a first entity of the second entities; and
a second content-associated metric is representative of online activity performed in association with one or more second content items, of the plurality of content items, associated with a second entity of the second entities;

processing, using a 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 content item associated with an entity of the second entities, a proportion of (i) activity performed in association with the content item by one or more users having an interest in an entity of the first entities relative to (ii) an entirety of activity performed in association with the content item;
generating an inferred activity distribution array by applying the plurality of content-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 machine learning model using the filtered subset of activity distribution values to generate a trained machine learning model; and
controlling transmission of content using the trained machine learning model.