التقنيات

Semantic Search

التعريف

A search approach that retrieves results based on the meaning and intent of a query rather than exact keyword matches. Semantic search is powered by embeddings and vector databases, enabling far more relevant enterprise knowledge retrieval.

مصطلحات ذات صلة

Embedding

A numerical representation of data (text, images, etc.) in a high-dimensional vector space where semantically similar items are mathematically close together. Embeddings are the foundational building block for semantic search, RAG pipelines, and recommendation systems.

Vector Database

A specialised database designed to store and efficiently search high-dimensional embedding vectors using approximate nearest-neighbour algorithms. Vector databases are the infrastructure backbone of RAG systems and semantic search applications.

Retrieval-Augmented Generation (RAG)

A technique that enhances LLM responses by retrieving relevant information from external knowledge sources before generating a response. RAG improves accuracy, reduces hallucinations, and enables LLMs to access up-to-date information without retraining.

خدمات ذات صلة

Product Decision Review

تحتاج مساعدة في فهم الذكاء الاصطناعي؟

احجز مكالمة تقييم ملاءمة Physical AI لمناقشة كيفية تطبيق مفاهيم الذكاء الاصطناعي هذه على قطاعك وتحدياتك.