Semantic Search Based on Embedding Models

Vanya Lazarova
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Vanya Lazarova: University of National and World Economy, Sofia, Bulgaria

Innovative Information Technologies for Economy Digitalization (IITED), 2025, issue 1, 111-115

Abstract: In this paper, very briefly the embedding models and the capabilities they provide for semantic search are introduced. In the paper is also presented the workflow of semantic search and the Semantic search in SQL database that are extended with data type VECTOR and the operations with vectors. The benefit for the end user is that he can find relevant documents in his organization's database by comparing query embeddings and documents.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:nwe:iitfed:y:2024:i:1:p:111-115

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