基于数据挖掘的教学信息分析技术研究

Research on Teaching Information Analysis Technology Based on Data Mining

针对高校教育输出和社会所需人才不对等的问题,设计一种基于Apriori优化算法和MapReduce结合的一种教学信息分析技术,将高校中一些非结构化数据进行离散化,计算支持度和可信度,挖掘出隐藏的决策信息,进而将其转换为有价值的数据,该方法可以解决海量数据优化分析,提高分析效率,有效克服高校教学信息分布的分散性、不均匀性,使得在线有价值信息能够高效获取,从而制定更适合学生的教学方法.通过实例证明了该算法在处理海量数据集时具有较高的效率.

Aiming at the problem of mismatch between the output of college education and talents needed by society,a teaching information analysis technology based on Apriori optimization algorithm and MapReduce is designed to discretize some unstructured data in colleges and universities,calculate the support and credibility,excavate the hidden decision information,and then convert it into valuable data.There is a method to solve the problem of massive,separation,and analysis,improve the efficiency of analysis,and effectively overcome the teaching meaning,information distribution,and unevenness of colleges and universities,so that online information can be efficiently obtained,so as to be more suitable for students teaching methods.In order to return to its own way.