Hybrid search is a technique that combines traditional keyword-based search with modern vector search to improve the relevance of search results. It can be beneficial for text-search use cases where both keyword matching and semantic search are important. By fusing the search results from both techniques, hybrid search can enhance the performance of a RAG pipeline.
Improving Retrieval Performance in RAG Pipelines with Hybrid Search
Search plays a crucial role in retrieving relevant information, but it can be challenging to achieve optimal performance. This article introduces the concept of hybrid search, a technique that combines traditional keyword-based search with modern vector search to improve search results’ relevance.
Hybrid search merges the advantages of both search techniques. Keyword-based search is excellent for specific terms, but it can miss important context due to typos and synonyms. On the other hand, vector or semantic search allows for multi-lingual and multi-modal search based on semantic meaning but can miss essential keywords.
By combining keyword-based and vector searches into a hybrid search, you can improve the performance of your RAG (Retrieval-Augmented Generation) pipeline. This technique enhances the relevance of search results, especially for text-search use cases.
To implement hybrid search, you need to fuse the search results from both techniques and re-rank them. This can be done by calculating scores based on metrics like cosine distance and weighting the scores with a parameter called alpha. Alpha determines the weighting between keyword-based and vector search, with values between 0 and 1.
Hybrid search is particularly useful in use cases where you want to enable semantic search capabilities for a more human-like search experience but still require exact phrase matching for specific terms. An example is Stack Overflow, which has implemented hybrid search to improve search results for coding problems.
Implementing hybrid search in your RAG pipeline can significantly enhance the relevance of retrieved context, leading to more accurate and valuable answers generated by the language model.
If you’re interested in exploring AI solutions for your company, consider leveraging hybrid search to improve search performance and enhance customer engagement. Reach out to us at hello@itinai.com for AI consultation and advice on implementing AI KPI management strategies.
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