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How does the BM25 algorithm prioritize search terms? - By giving higher importance scores to terms that appear less frequently across documents
What is the main difference between semantic search and lexical search? - Semantic search uses embeddings to understand meaning, while lexical search looks for exact term matches
What is a vector database optimized for? - Storing, comparing, and searching through numerical embeddings
What is Retrieval Augmented Generation (RAG)? - A technique that breaks large documents into chunks and retrieves only relevant pieces when answering questions.
What problem does contextual retrieval solve in RAG systems? - Chunks losing their connection to the broader document context when split
What is a text embedding? - A numerical representation of the meaning contained in text.
What is Reciprocal Rank Fusion (RRF) used for in RAG systems? - Merging and ranking results from multiple search methods.
When would structure-based chunking work best for your document? - When you have well-formatted documents with clear headers and sections
What is the main difference between semantic search and lexical search? - Semantic search uses embeddings to understand meaning, while lexical search looks for exact term matches
What is a vector database optimized for? - Storing, comparing, and searching through numerical embeddings
What is Retrieval Augmented Generation (RAG)? - A technique that breaks large documents into chunks and retrieves only relevant pieces when answering questions.
What problem does contextual retrieval solve in RAG systems? - Chunks losing their connection to the broader document context when split
What is a text embedding? - A numerical representation of the meaning contained in text.
What is Reciprocal Rank Fusion (RRF) used for in RAG systems? - Merging and ranking results from multiple search methods.
When would structure-based chunking work best for your document? - When you have well-formatted documents with clear headers and sections