Evaluating Retrieval-Based Chatbot Systems: A Focus on Speed and Performance

This paper explores the design and evaluation ofretrieval-based chatbots, emphasizing practical performanceindicators and inference speed in industrial applications. Webegin by outlining the structure of retrieval-based dialog systems,including fine-grained ranking and coarse-grained candidate setgeneration. Experiments are conducted using the Douban datasetto assess the effectiveness of the Faiss library in optimizingretrieval speeds. We present comparative results of state-of-theart methods, followed by a critical analysis of the challenges andfuture trends in retrieval-based systems, particularly focusing onsemantic matching, inference speed, and scaling to large datasets.