In the context of AI and search, a vector is a numerical representation of text – like a word, sentence, or paragraph – converted into a multi-dimensional space. This process, called embedding, allows complex content to be compared based on meaning rather than exact wording.
Unlike traditional keyword matching, vectors enables semantic search, meaning the search system can understand and retrieve results that are relevant even if they don’t use the exact same words as the query.
SearchRovr uses vector embeddings behind the scenes to match a user’s natural-language query with the most semantically relevant content from your WordPress site. This makes your on-site search smarter and more intuitive, especially when dealing with synonyms, varied phrasing, or complex questions.