> ## Documentation Index
> Fetch the complete documentation index at: https://wiki.platelunchcollective.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Sparse Retrieval

> Sparse retrieval is a method of information retrieval that matches documents to queries based on keyword frequency and overlap — using techniques like TF-IDF...

*Technical implementation* · *AI Search Infrastructure*

## Definition

Sparse retrieval is a method of information retrieval that matches documents to queries based on keyword frequency and overlap — using techniques like TF-IDF and BM25. It is called "sparse" because the vector representations it uses contain mostly zeros, with non-zero values only for terms that appear in the document.

## Why It Matters for AI Search

Sparse retrieval is the technology that traditional keyword search is built on — and it is increasingly being supplemented or replaced by dense retrieval in AI search systems. Understanding sparse retrieval matters because many AI systems use hybrid retrieval — combining dense and sparse signals — rather than relying on embeddings alone. Content that is both semantically rich and uses precise, domain-relevant terminology performs well in both retrieval modes.

## Related Terms

<CardGroup cols={2}>
  <Card title="Dense retrieval" href="/ai-search-glossary/dense-retrieval" />

  <Card title="BM25" href="/ai-search-glossary/bm25" />

  <Card title="TF-IDF" href="/ai-search-glossary/tf-idf" />

  <Card title="Keyword search" href="/ai-search-glossary/keyword-search" />

  <Card title="Hybrid retrieval" href="/ai-search-glossary/hybrid-retrieval" />
</CardGroup>

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