Content recommendation based upon continuity and grouping information of attributes

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:
• populating a data structure with user interaction data specifying whether users interacted with content items, user attributes of the users, and content attributes of the content items, wherein user attribute values of a user attribute are populated within a first set of fields, content attribute values of a content attribute are populated within a second set of fields, and user interaction indicator values are populated within a third set of fields;
• modifying the data structure by inserting a set of sub-fields for the user attribute, wherein a sub-field is populated with a value representing an option of the user attribute and the set of sub-fields are an encoding of continuity information and grouping information representing options for the user attribute;
• processing the data structure using machine learning functionality to generate a model;
• and
• utilizing the model to generate a prediction as to whether a user will interact with a content item.

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

• populating a data structure with user interaction data specifying whether users interacted with content items, user attributes of the users, and content attributes of the content items, wherein user attribute values of a user attribute are populated within a first set of fields, content attribute values of a content attribute are populated within a second set of fields, and user interaction indicator values are populated within a third set of fields;
• modifying the data structure by inserting a set of sub-fields for an attribute, wherein the set of sub-fields are an encoding with gray code information and grouping information corresponding to options for the attribute, wherein the attribute comprises at least one of a user attribute or a content attribute;
• processing the data structure using machine learning functionality to generate a model;
• and
• utilizing the model to generate a prediction as to whether a user will interact with a content item.