Cloud-network convergence, as an emerging technology in the service computing domain, has created novel development prospects for network services. Understanding user intent constitutes a key component in this technological framework, yet existing research efforts remain substantially inadequate in addressing this critical aspect, necessitating in-depth investigation. This study therefore focuses on the analytical investigation of user service intent data within cloud-network convergence environments, establishing a comprehensive service intent interpretation and translation framework to facilitate the proactive transformation of Internet-related services. To address the challenge of directly acquiring user intent information identified in current research, this paper proposes an integrated solution framework. Specifically targeting the prevalent issue of data scarcity in network intent datasets within cloud-network convergence systems, the present research develops a novel dataset generation scheme for user service intent characterization.