Embedding space

An embedding space is a latent vector space where items such as words, documents, images, users, or products are represented as numerical coordinates. Items with related meanings or features are positioned near one another, which lets models compare similarity, retrieve neighbors, cluster concepts, and perform operations such as interpolation or vector addition.

“A search system can embed both a question and an article into the same embedding space, then retrieve the article whose vector is closest to the question.”