AIF-C01 Practice Question 98: Hybrid Search Exact Identifiers

AWS Certified AI Practitioner (AIF-C01) · Test 10 · question 8 of 10

Applications of Foundation Modelsmedium

An engineering team's Amazon Bedrock knowledge base stores support documentation in an Amazon OpenSearch Serverless vector store. When a user searches for an exact error code such as "ERR-4471-B", retrieval returns documents about similar-sounding errors instead of the page that contains that exact code. The knowledge base is currently set to semantic search only, and the team still wants semantic matching for natural-language questions. What should they configure?

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Answer:

B. Hybrid search (vector plus keyword)

A knowledge base supports two search strategies. Semantic *"only searches vector embeddings"*, which finds text with similar meaning but can miss exact tokens such as product codes. Hybrid *"combines searching vector embeddings (semantic search) with searching through the raw text"*, so an exact identifier matches on keywords while natural-language questions still benefit from semantic similarity (option B). Hybrid search is supported for Amazon RDS, Amazon OpenSearch Serverless and MongoDB vector stores that contain a filterable text field.

- A is wrong because the current semantic-only search is what causes the problem: embeddings put "similar-sounding" errors close together, and returning more chunks does not guarantee that the exact-string match is among them. - C is wrong because temperature affects generation, after retrieval. The wrong pages would still be retrieved. - D is wrong because larger chunks contain more mixed content, which dilutes an exact code further rather than making it easier to match.

Reference: Configure and customize queries and response generation

Practice Test 10 ›

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