Embedding
A numerical representation of text that captures its semantic meaning.
Definition
In AI and machine learning, an embedding is a numerical vector representation of text (or other data) that captures its semantic meaning. Texts with similar meanings have similar embeddings, even if they use different words. Embeddings enable semantic search by allowing systems to find content based on meaning rather than exact keyword matches. They are fundamental to RAG systems and modern search technologies.
More in Data Infrastructure
Chunking
Splitting documents into smaller segments for processing and retrieval.
Vector Database
A database optimised for storing and querying high-dimensional vector data.
Knowledge Graph
A structured representation of entities and their relationships.
Reranking
Reordering search results using a more sophisticated model to improve relevance.
See Embedding in action
Understanding the terminology is the first step. See how Conductor applies these concepts to solve real document intelligence challenges.
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