Is <scp>AIGC</scp> Technology Useful? A Comparative Analysis of Search Technologies for Online Museums

ABSTRACT This study explored whether the application of generative search (GS) techniques—including RAG, COT, and RAT—is superior to traditional keyword search (KS) techniques in digital museum scenarios. We constructed a prototype search system using 800 painting collections from the digital collection repository platform of the Palace Museum in Beijing. Sixteen users performed factual, explanatory, and exploratory search tasks while evaluating five search methods, including KS and various GS optimizations. The experiment results reveal that GS performs better than KS, despite challenges with user satisfaction and search accuracy because of vague responses and occasional hallucinations. Among GS techniques, RAT—integrating chain‐of‐thought reasoning with document retrieval—achieved the best overall performance. The findings help overcome current search challenges in digital cultural heritage and provide practical guidance for advancing the intelligent development of online museums.