An embedding is a mathematical representation of data (such as text, images, or audio) transformed into a dense vector (a list of numbers) that captures the semantic meaning or relationships between items. In natural language processing (NLP), embeddings allow machines to understand context, similarity, and meaning across words, sentences, or entire documents.
In the context of SearchRovr, embeddings are used to convert your site’s content and a user’s search query into comparable vectors. This enables semantic search, allowing the AI to return relevant results even when the exact words don’t match – improving both accuracy and user experience.