云计算环境下电子政务大数据系统填补及分类算法

Filling and classification algorithm for e⁃government big data system in cloud computing environment

传统的电子政务大数据系统填补及分类算法准确率低,工作效率差。为了解决这一问题,在云计算环境下研究了一种新的电子政务大数据系统填补及分类算法,在完备相容理论基础上进行电子政务大数据填补,将电子政务大数据系统填补算法架构在云计算平台上,以此将数据并行化,通过决策树进行数据分类,实现增量更新决策森林并行化处理。为验证方法效果,设定对比实验,结果表明,提出的电子政务大数据系统填补及分类算法能够在短时间内实现填补和分类,具有很强的工作能力。

The traditional e⁃government big data system filling and classification algorithms have low classification accuracy and poor work efficiency.In order to solve this problem,a new e⁃government big data system filling and classification algorithm classification is researched in the cloud computing environment.The e⁃government big data filling is based on a complete and compatible theory.The architecture is built on a cloud computing platform to parallelize the data and classify the data through a decision tree to achieve parallel processing of incremental update decision forests.In order to verify the effectiveness of the method,a comparative experiment is set up.The results show that the proposed e⁃government big data system filling and classification algorithm classification can achieve filling and classification in a short time and has a strong working ability.