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Multiple parameter cluster analysis in a multiple language learning system

机译:多语言学习系统中的多个参数聚类分析

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In this paper, we present our multiple parameter cluster analysis in our multiple language learning system. Towards this direction, we have used algorithmic approaches residing in the field of machine learning. Multiple parameter cluster analysis is conducted by the k-means clustering algorithm which takes as input seven important users' characteristics in order to initialize the process. The clustering is conducted by k-means clustering algorithm, which takes as input multiple user characteristics. The incorporation of k-means clustering is used to address several barriers posed by the heterogeneous learning audience of educational systems. After determining in which cluster each new student belongs, the system can reason about this specific student, adapting its behavior to the student's needs, performance and preferences.
机译:在本文中,我们在多语言学习系统中展示了我们的多个参数集群分析。朝向这个方向,我们使用驻留在机器学习领域的算法方法。多个参数聚类分析由K-means群集算法进行,它以输入七个重要用户的特征为才能初始化该过程。群集由K-means聚类算法进行,其作为输入多用户特性。 k-means聚类的纳入用于解决受教育系统异构学习观众构成的几个障碍。在确定每个新生所属的集群之后,系统可以推理这个特定的学生,将其行为适应学生的需求,性能和偏好。

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