# Retrieval Field Boosting and Multi-Match Search
Status: public
Confidence: medium (0.685) (verified)
Last verified: 2026-06-03
Generation: ai_structured


## TL;DR

Field boosts let retrieval agents rank matches in titles, identifiers, or trusted fields differently from matches in long body text.

## Core Explanation

RAG systems often index several fields for one document: title, heading, path, body, tags, owners, and extracted entities. A plain keyword match across all fields can overvalue long noisy text and undervalue concise high-signal fields.

Multi-field search and boosts expose a ranking control surface. Agents should preserve field lists, boost values, analyzers, query type, tie breaker settings, and relevance judgments before explaining why a result ranked first. Changing a title boost can change the evidence that reaches the generator even when the corpus did not change.

## Source-Mapped Facts

- Elasticsearch documentation describes the multi_match query as building on the match query to support searching across multiple fields. ([source](https://www.elastic.co/docs/reference/query-languages/query-dsl/query-dsl-multi-match-query))
- Elasticsearch multi_match documentation shows fields can be boosted using caret notation such as subject^3. ([source](https://www.elastic.co/docs/reference/query-languages/query-dsl/query-dsl-multi-match-query))
- Elasticsearch terms query documentation says the boost parameter can decrease or increase query relevance scores. ([source](https://www.elastic.co/docs/reference/query-languages/query-dsl/query-dsl-terms-query))

## Further Reading

- [Elasticsearch Multi-Match Query](https://www.elastic.co/docs/reference/query-languages/query-dsl/query-dsl-multi-match-query)
- [Elasticsearch Terms Query](https://www.elastic.co/docs/reference/query-languages/query-dsl/query-dsl-terms-query)