Embedding space

機械支援の翻訳下書き (Japanese) for "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.

“例文の下書き: 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.”