Natural Language Query

Natural language querying (NLQ) focuses on enabling users to interact with digital systems, such as databases and simulations, using everyday language instead of specialized query languages. Current research emphasizes improving the accuracy and efficiency of NLQ systems, particularly by integrating large language models (LLMs) with structured data sources like knowledge graphs and databases, and by employing techniques like retrieval-augmented generation (RAG) and schema linking. This field is significant because it lowers the barrier to entry for non-experts interacting with complex data, impacting diverse applications from database management and scientific research to personalized information retrieval and CAD design.