A Classification Method of Tourism English Talents Based on Feature Mining and Information Fusion Technology

With the rapid development of the Internet, text data has become one of the major formats of big data tourism and improves the quality and promotes the optimization and upgradation of tourism English talents. This paper proposes a model of tourism English talent resources based on data mining techniques using a big data framework. The characteristic distribution structure model is built to identify and blend the characteristics of tourism English talent resources. Connection feature mining and information fusion are combined to share data and schedule resources during the talent training process. Initially, the proposed research work uses a cloud storage system for developing intercultural communicative competence of tourism English talents. Next, the optimal scheduling design of tourism English talent training resource’s big data is carried out. Finally, the fuzzy clustering method deals with the adaptive clustering of tourism English talent resource distribution big data. The simulation findings show that the proposed method has high precision and big data computation efficiency. Moreover, it can successfully mentor the development of a new framework of tourism English talent training.