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Research on Application of Data Mining in Virtual Community of Foreign Language Learning

机译:数据挖掘在外语学习虚拟社区中的应用研究

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摘要

The construction of virtual community in foreign language learning is a comprehensive foreign language learning environment integrated with foreign language vocabulary database construction and vocabulary retrieval, combining the virtual reality technology to construct the language environment of foreign language learning. The virtual community of foreign language learning can improve the sense of language authenticity in foreign language learning and improve the quality of foreign language teaching. A method of building a virtual community for foreign language learning is proposed based on data mining technology, data acquisition and feature preprocessing model for building semantic vocabulary of foreign language learning is constructed, the linguistic environment characteristics of the semantic vocabulary data of foreign language learning is analyzed, and the semantic noumenon structure model is obtained. Fuzzy clustering method is used for vocabulary clustering and comprehensive retrieval in the virtual community of foreign language learning, the performance of vocabulary classification in foreign language learning is improved, the adaptive semantic information fusion method is used to realize the vocabulary data mining in the virtual community of foreign language learning, information retrieval and access scheduling for virtual communities in foreign language learning are realized based on data mining results. The simulation results show that the accuracy of foreign language vocabulary retrieval is good, improve the efficiency of foreign language learning.
机译:外语学习虚拟社区的建设是一个综合的外语学习环境,结合了外语词汇数据库的建设和词汇检索,结合虚拟现实技术构建了外语学习的语言环境。外语学习虚拟社区可以提高外语学习中的语言真实感,提高外语教学质量。提出了一种基于数据挖掘技术构建外语学习虚拟社区的方法,构建了数据获取和特征预处理模型,用于构建外语学习的语义词汇,建立了外语学习语义词汇数据的语言环境特征。分析,得到语义本体结构模型。模糊聚类法用于外语学习虚拟社区中的词汇聚类和综合检索,提高了外语学习中词汇分类的性能,自适应语义信息融合方法实现了虚拟社区中词汇数据的挖掘基于数据挖掘的结果,实现了外语学习中虚拟社区的信息检索和访问调度。仿真结果表明,外语词汇检索的准确性良好,提高了外语学习效率。

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