Abstract: Methods, systems, and computer-readable storage media for improving the accuracy of embedding vector generation for domain-specific text for purposes of semantic search and generative AI. A dictionary of domain-specific terms can be built to include embedding vectors generated for respective domain-specific terms using a pre-trained large language model. A list of domain-specific terms pertaining to a particular domain can be identified and textual content comprising a description or a definition of a respective domain-specific term can be obtained. A domain-adapted embedding vector for each domain-specific term can be generated based on the textual content for that term. The domain-specific dictionary can be built to include a combination of a domain-specific term, a corresponding domain-adapted embedding vector and the domain-specific term definition or description.

Abstract: Methods, systems, and computer-readable storage media for improving the accuracy of embedding vector generation for domain-specific text for purposes of semantic search and generative AI. A dictionary of domain-specific terms can be built to include embedding vectors generated for respective domain-specific terms using a pre-trained large language model. A list of domain-specific terms pertaining to a particular domain can be identified and textual content comprising a description or a definition of a respective domain-specific term can be obtained. A domain-adapted embedding vector for each domain-specific term can be generated based on the textual content for that term. The domain-specific dictionary can be built to include a combination of a domain-specific term, a corresponding domain-adapted embedding vector and the domain-specific term definition or description.