Systems and methods for determining entity attribute representations

A system comprising:

• one or more processors;
• and
• memory comprising computer code, which when executed by the one or more processors, causes the system to:
• provide, to a first machine learning model, entity information for each of a plurality of entities, wherein the first machine learning model has been trained to generate an entity numerical representation for each of the plurality of entities based on the respective entity information of the entity;
• determine, by the trained first machine learning model, a plurality of entity numerical representations based on received respective entity information for the plurality of entities, wherein the entity numerical representation comprises a numerical representation of the information related to the entity;
• receive an entity search text from a computing device;
• provide the entity search text to the trained first machine learning model to generate query numerical representation of the entity search text;
• compare the query numerical representation with each of the plurality of entity numerical representations to determine a similarity score indicating a similarity between the query numerical representation and a respective entity numerical representation;
• and
• based on the determined similarity scores, identify an entity numerical representation most similar to the entity search text,
• wherein the comparing the query numerical representation with each of the plurality of entity numerical representations is performed by a matrix multiplication operation.

A machine-readable medium storing computer readable code, which when executed by one or more processors is configured to perform operations including:

• providing, to a first machine learning model, entity information for each of a plurality of entities, wherein the first machine learning model has been trained to generate an entity numerical representation for each of the plurality of entities based on the respective entity information of the entity;
• determining, by the trained first machine learning model, a plurality of entity numerical representations based on received respective entity information for the plurality of entities, wherein the entity numerical representation comprises a numerical representation of the information related to the entity;
• receiving an entity search text from a computing device;
• providing the entity search text to the trained first machine learning model to generate query numerical representation of the entity search text;
• comparing the query numerical representation with each of the plurality of entity numerical representations to determine a similarity score indicating a similarity between the query numerical representation and a respective entity numerical representation;
• and
• based on the determined similarity scores, identifying an entity numerical representation most similar to the entity search text,
• wherein the comparing the query numerical representation with each of the plurality of entity numerical representations is performed by a matrix multiplication operation.