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.

中文翻译：

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基于特征挖掘和信息融合技术的旅游英语人才分类方法

随着互联网的飞速发展，文本数据已成为大数据旅游的主要形式之一，它提高了质量，促进了旅游英语人才的优化和提升。基于大数据框架的数据挖掘技术，提出了一种旅游英语人才资源模型。建立特征分布结构模型，以识别和融合旅游英语人才资源的特征。在人才培训过程中，连接特征挖掘和信息融合相结合以共享数据和调度资源。最初，拟议的研究工作使用云存储系统来发展旅游英语人才的跨文化交际能力。其次，进行了旅游英语人才培养资源大数据的优化调度设计。最后，模糊聚类方法处理旅游英语人才资源分布大数据的自适应聚类。仿真结果表明，该方法具有较高的精度和较大的数据计算效率。而且，它可以成功地指导新的旅游英语人才培训框架的开发。