Author(s): Alok Choudhary

Originally published on Towards AI.

A complete breakdown of hybrid search architecture, reciprocal rank fusion, and graph knowledge search for developers.

When we build RAG (Retrieval-Augmented Generation) applications, the way we search and retrieve information makes a huge difference in the quality of responses we get. Most RAG systems rely on just one type of search, but there’s a more powerful approach called Hybrid Search that combines multiple techniques to give better results.

Hybrid search significantly improves information retrieval by combining both semantic and syntactic search methods, resulting in more relevant results for various applications. This method merges different search techniques to create a more robust data retrieval system, integrating reciprocal rank fusion to enhance the ranking of documents based on their relevance to user queries. Additionally, hybrid search is increasingly utilized in real-world applications, including e-commerce, where understanding user intent alongside specific queries is crucial for delivering accurate search outcomes.

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Published via Towards AI