System and method for feature determination and content selection

A computing device comprising:

• a processor;
• and
• memory comprising processor-executable instructions that when executed by the processor cause performance of operations, the operations comprising:
• determining a plurality of user-associated metrics associated with first entities in which one or more users have an interest, 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 model, first vector representations associated with the first entities in which one or more users have an interest and second vector representations associated with second entities associated with one or more content items to generate an attention distribution array, wherein each value of the attention distribution array is based upon, for a user interested in an entity of the first entities in which one or more users have an interest, both (i) entity-specific activity, of the user, related to an entity of the second entities associated with one or more content items and (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;
• training a machine learning model using the inferred activity distribution array to generate a trained machine learning model;
• and
• controlling transmission of content using the trained machine learning model.

A non-transitory machine readable medium having stored thereon processor-executable instructions that when executed cause performance of operations, the operations comprising:

• determining a plurality of content-associated metrics associated with second entities associated with one or more content items, wherein:
• a first content-associated metric is representative of online activity performed in association with one or more first 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 associated with a second entity of the second entities;
• processing, using a model, first vector representations associated with first entities in which one or more users have an interest and second vector representations associated with the second entities associated with one or more content items to generate an attention distribution array, wherein each value of the attention distribution array is based upon, for a content item associated with an entity of the second entities associated with one or more content items, both (i) activity performed in association with the content item by one or more users having an interest in an entity of the first entities in which one or more users have an interest and (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;
• training a machine learning model using the inferred activity distribution array to generate a trained machine learning model;
• and
• controlling transmission of content using the trained machine learning model.