Hybrid search is a distinct method which integrates various types of searches into a single query. Traditional search, also known as keyword or lexical search, works with textual data and identifies text through direct matches, whether complete or partial.
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Understanding Hybrid Search with Azure AI Search
Azure AI Search enables hybrid search by allowing vector fields with embeddings to coexist with standard textual data in the same document.
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Reciprocal Rank Fusion (RFF)
Azure AI Search’s ability to perform hybrid searches isn’t solely due to its support for both textual data and embeddings. After completing both search types, the results need to be unified before being returned in a response. Azure AI Search uses the Reciprocal Rank Fusion (RRF) algorithm to achieve this.
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Identifying the Impact of Weighted Scores
You can weight vector queries before using them in RRF ranking. Since the same query is used in multiple searches before combining them, the score for each search type may not have the same weight or relevance. A keyword search that produces a perfect score for a query should be assessed differently from a vector search that scored around 0.8.
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This content was released on Nov 15 2024. The official support period is 6-months
from this date.
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