Semantic Search

Semantic Search is an advanced search technology that understands the meaning, intent, and context behind search queries rather than simply matching keywords. Unlike traditional keyword-based search that looks for exact word matches, semantic search uses natural language processing and machine learning to comprehend the conceptual meaning of both the query and the content being searched. This enables more accurate and relevant results by understanding synonyms, related concepts, and contextual relationships. Semantic search systems typically use vector embeddings to represent both queries and documents in a high-dimensional space where semantically similar items are positioned close to each other. This technology powers modern search engines, recommendation systems, and AI assistants, enabling them to return more relevant results even when the query doesn't contain exact keywords found in the target content. Semantic search is particularly valuable in enterprise applications where users may express the same concept in different ways or when searching across diverse content types and domains.