Using Data Mining Techniques in Web-Based Instruction Data Analysis

M. Yao, Xi-zi Jin, Na Wang
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Abstract

In order to solve practical problems in network teaching data analysis ,the web-based instruction data of mathematical models and model framework was build .In the core process that data scoop out, the main adoption the classification method based on the continuity of data.It firstly gains the class-contained from the sample, and then obtains the standard category through the degree of support, finally marks the degree of strength among the inside members. This approach is only sensitive to the even distribution of the inside sample points, it does not require pre-set parameters . Using the clustering method analysis the web-based instruction data, the problem of web-based instruction data automatically cluster was solved.
数据挖掘技术在基于web的教学数据分析中的应用
为了解决网络教学数据分析中的实际问题,建立了基于web的教学数据数学模型和模型框架,在数据挖掘的核心过程中,主要采用基于数据连续性的分类方法。首先从样本中得到所含的类别,然后通过支撑度得到标准类别,最后标记内部构件之间的强度程度。这种方法只对样本内点的均匀分布敏感,不需要预先设置参数。利用聚类方法对基于web的教学数据进行分析,解决了基于web的教学数据自动聚类的问题。
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