What is Semantic Search?
A search method that uses embeddings to understand the meaning behind queries and documents, enhancing retrieval relevance.
More about Semantic Search:
Semantic Search is a method that goes beyond keyword matching to understand the intent and meaning behind user queries. It leverages embeddings generated by models like contextual embeddings to perform similarity-based matching between queries and documents.
Semantic search is widely used in retrieval augmentation pipelines, recommendation systems, and knowledge retrieval, providing accurate and context-aware results for user queries.
Frequently Asked Questions
How does semantic search improve traditional search methods?
It captures the meaning and intent of queries, making retrieval more accurate and contextually relevant compared to sparse retrieval.
What technologies power semantic search?
Technologies like dense retrieval, embeddings, and vector databases are integral to semantic search systems.
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