Exploring the use of graph and vector search in retrieval-augmented generation (RAG) systems, focusing on their application in financial analysis. Discusses the differences between graph and vector search, optimization levers for graph search, and the combination of both methods in RAG. Highlights the benefits of graph databases for modeling complex relationships and dependencies, as well as the limitations and complementarity of vector search. Demonstrates the application of graph and vector search in a financial report RAG example.

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Answer Completeness and Limitations of Graph and Vector QueryingDepth Questions

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