Keyword-Search

Dense vectors are magical at capturing semantics, but they fail when you need exact matches. This article unpacks the Vocabulary Mismatch Problem and introduces SPLADE—a neural approach that combines the precision of keyword search with the intelligence of transformers. Learn why sparse embeddings matter and how to architect hybrid search for production.

Conventional keyword search matches user query words to document words using an inverted index data structure for efficient matching and ranking by relevancy.

Retrieval is the backbone of RAG. We explore the critical steps often missed by developers: proper chunking strategies, the ‘Librarian’ analogy for vector vs. keyword search, and solving the math problem of Hybrid Search using Reciprocal Rank Fusion (RRF).