An encoder maps text, images, or other items into fixed-length vectors learned from data. Similarity measures over those vectors support semantic retrieval, clustering, recommendation, and classification.
A vector embedding is a numeric representation designed so meaningful relationships can be compared with geometry.
An encoder maps text, images, or other items into fixed-length vectors learned from data. Similarity measures over those vectors support semantic retrieval, clustering, recommendation, and classification.