Why Your Search Bar Understands You

Short summary

Semantic search understands meaning rather than just keywords by converting words into numerical embeddings—coordinates in 'meaning-space' where similar concepts cluster together. For example, 'comfy shoes for standing' matches nursing clogs despite minimal word overlap because both occupy the same semantic region. The engine uses k-nearest neighbor algorithms to rank results by proximity in meaning-space, with context and user intent shaping which interpretation wins.

• •Embeddings convert words into numerical coordinates in semantic space where similar meanings cluster
• •Results ranked by proximity to query in meaning-space rather than keyword matching
• •Context and user intent disambiguate meaning, enabling search to return relevant results even with zero word overlap

Generated with AI, which can make mistakes.