US 2025/0053586 A1 · AUTOMATED DOMAIN ADAPTATION FOR SEMANTIC SEARCH USING EMBEDDING VECTORS

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.

Claims18

Dependent claims

A computer-implemented method for building a domain-specific vector search database for a domain-specific store, the domain-specific vector search database comprising embedding vectors corresponding to domain-specific terms, the method comprising:

obtaining content pieces included in the domain-specific store pertaining to a particular domain;
for each content piece,
identifying domain-specific terms in a respective content piece;
obtaining domain-adapted embedding vectors corresponding to the domain-specific terms as identified in the content piece, and
generating a generic embedding vector corresponding to the respective content piece using a large language model, and
combining the generic embedding vector with the domain-adapted embedding vectors to provide a combined domain-adapted embedding vector for the respective content piece;
and
storing the content pieces indexed with combined domain-adapted embedding vectors into the domain-specific vector search database to be used for executing semantic searching.

5 more elements

A non-transitory computer-readable storage medium coupled to one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations, the operations comprising:

obtaining content pieces included in a domain-specific store pertaining to a particular domain;
for each content piece,
identifying domain-specific terms in a respective content piece;
obtaining domain-adapted embedding vectors corresponding to the domain-specific terms as identified in the content piece, and
generating a generic embedding vector corresponding to the respective content piece using a large language model, and
combining the generic embedding vector with the domain-adapted embedding vectors to provide a combined domain-adapted embedding vector for the respective content piece;
and
storing the content pieces indexed with combined domain-adapted embedding vectors into a domain-specific vector search database to be used for executing semantic searching.

5 more elements

A system, comprising:

a computing device;
and
a computer-readable storage device coupled to the computing device and having instructions stored thereon which, when executed by the computing device, cause the computing device to perform operations, the operations comprising:
obtaining content pieces included in a domain-specific store pertaining to a particular domain;
for each content piece,
identifying domain-specific terms in a respective content piece;
obtaining domain-adapted embedding vectors corresponding to the domain-specific terms as identified in the content piece, and
generating a generic embedding vector corresponding to the respective content piece using a large language model, and
combining the generic embedding vector with the domain-adapted embedding vectors to provide a combined domain-adapted embedding vector for the respective content piece;
and
storing the content pieces indexed with combined domain-adapted embedding vectors into a domain-specific vector search database to be used for executing semantic searching.

8 more elements

Dependencies are inferred from the claim text.

Automated domain adaptation for semantic search using embedding vectors

Life of this patent

Automated domain adaptation for semantic search using embedding vectors

Life of this patent

Abstract

Claims18