Contemporary product user demand exhibits dynamic and diversified characteristics, making the effective identification of product innovation opportunities from dynamically evolving demand data a critical challenge. To address this issue, a method for product opportunity identification and innovation strategy generation based on the dynamic evolution analysis of demand is proposed by integrating the Large Language Model (LLM) and the Temporal Graph Convolutional Network (TGCN).
