Artificial intelligence-based methods and systems for generating optimal embeddings for identifying similar entities

A server system, comprising:

• a memory configured to store instructions;
• a communication interface;
• and
• a processor in communication with the memory and the communication interface, the processor configured to execute the instructions stored in the memory and thereby cause the server system to perform at least in part to:
• access an entity-related dataset from a database associated with the server system, the entity-related dataset comprising information related to a plurality of entities;
• generate a set of entity-specific features corresponding to each of the plurality of entities based, at least in part, on the entity-related dataset, the set of entity-specific features comprising a subset of numerical features and a subset of categorical features;
• determine a label corresponding to each of the plurality of entities based, at least in part, on the subset of categorical features;
• generate via a first machine learning model, a first set of entity-specific embeddings corresponding to each of the plurality of entities based, at least in part, on the corresponding subset of numerical features and the corresponding label;
• generate via a second machine learning model, a second set of entity-specific embeddings corresponding to each of the plurality of entities based, at least in part, on the corresponding subset of categorical features and the corresponding first set of entity-specific embeddings;
• and
• generate a set of optimal embeddings corresponding to each of the plurality of entities based, at least in part, on concatenating the corresponding first set of entity-specific embeddings and the corresponding second set of entity-specific embeddings.

A non-transitory computer-readable storage medium comprising computer-executable instructions that, when executed by at least a processor of a server system, cause the server system to perform a method comprising:

• accessing an entity-related dataset from a database associated with the server system, the entity-related dataset comprising information related to a plurality of entities;
• generating a set of entity-specific features corresponding to each of the plurality of entities based, at least in part, on the entity-related dataset, the set of entity-specific features comprising a subset of numerical features and a subset of categorical features;
• determining a label corresponding to each of the plurality of entities based, at least in part, on the subset of categorical features;
• generating via a first machine learning model, a first set of entity-specific embeddings corresponding to each of the plurality of entities based, at least in part, on the corresponding subset of numerical features and the corresponding label;
• generating via a second machine learning model, a second set of entity-specific embeddings corresponding to each of the plurality of entities based, at least in part, on the corresponding subset of categorical features and the corresponding first set of entity-specific embeddings;
• and
• generating a set of optimal embeddings corresponding to each of the plurality of entities based, at least in part, on concatenating the corresponding first set of entity-specific embeddings and the corresponding second set of entity-specific embeddings.