Boosting chat responses using metadata boosting

If you choose to use an Amazon Q Business native retriever, you can assign weights to document attributes after mapping them to Amazon Q Business index fields using the Amazon Q Business metadata boosting feature. Then, you can use these assigned weights to fine-tune the underlying ranking of RAG retrieved passages within your Amazon Q application environment to optimize the relevance of chat responses. In Amazon Q, boosting means to raise a document in chat results using these weights.

Boosting chat responses based on document attributes helps you rank sources that are more authoritative higher than other sources in your application environment. You can assign a higher value to more recent content, specific file types, or specific data sources.

Amazon Q Business automatically boosts specific document attributes, like document title, when retrieving information from your index to generate end user chat responses. You can use the boosting feature to customize and control boosting, and also override any pre-existing boosts applied by Amazon Q Business.

When you use this feature, a Retrieval Augmented Generation (RAG)-generated result is given a boost during retrieval when the query includes terms that match that field or attribute. You specify how much of a boost the document receives when there is a match. When Amazon Q Business generates responses, it prioritizes the sources that are assigned higher rankings.

Choosing to boost document attributes doesn't by itself cause Amazon Q Business to include or exclude a document in the chat response. A boosted document attribute is only one of the factors that Amazon Q Business uses to determine the relevance of a document.