Abstract: Systems and methods are disclosed herein for creating and continuously improving domain-specific translation models using synthetic data. The systems and methods can include creating a domain-specific translation model for product naming conventions, training the domain-specific translation model, and translating an arbitrary product name to a standardized product descriptor using the trained domain-specific translation model. The system can include a canonical reference ontology (CRO) defining a canonical ontology for a given domain, a generative AI model for creating synthetic training data based on the CRO, and a domain-specific translation model. The methods can include training the domain-specific translation model with the synthetic training data to translate arbitrary product names to standardized product descriptors for the domain.

Abstract: Systems and methods are disclosed herein for creating and continuously improving domain-specific translation models using synthetic data. The systems and methods can include creating a domain-specific translation model for product naming conventions, training the domain-specific translation model, and translating an arbitrary product name to a standardized product descriptor using the trained domain-specific translation model. The system can include a canonical reference ontology (CRO) defining a canonical ontology for a given domain, a generative AI model for creating synthetic training data based on the CRO, and a domain-specific translation model. The methods can include training the domain-specific translation model with the synthetic training data to translate arbitrary product names to standardized product descriptors for the domain.