采用云计算的数据挖掘技术可视化教学与实验方案

Teaching and Experimental Schema of Data Mining Technology Combined with the Cloud Computing

针对数据挖掘技术较为抽象并且难以理解等问题,设计了数据挖掘课程的教学与实验方案。方案包含了数据分类、聚类、降维以及关联规则等数据挖掘子技术。将传感器、互联网、社交媒体等不同类型的数据作为实验数据集,采用云计算技术提高计算与存储的效果,提高教学与实验的效率。设计了图形交互界面,能够以图形形式与表格输出数据分类、聚类、降维以及关联规则的结果,提高数据挖掘技术的可理解性。数据挖掘的实验结果表明,本方案能够准确生成数据挖掘技术的散列图,可直观地观察数据挖掘的工作流程。

The technology of data mining is abstract and difficult to be understood,a teaching and experimental schema of data mining technology is designed to resolve that problem. The proposed schema includes data classification,data clustering,data dimensionality reduction and association rules. Datasets of different types are used as the experimental datasets including sensors datasets,Internet datasets and social media datasets,at the same time,cloud computing technology is adopted to improve the efficiency of computation and storage,so that the efficiency of lessons and experiments is improved too. Graphic interface is designed to generate the graph and table results of data classification,data clustering, data dimensionality and association rules, and it makes the data mining technology easy to be understood. Lastly,experimental results of data mining show that the proposed schema generates accuracy plot graphs of data mining technologies,and makes the data mining workflow visual.