大数据中心存储信息分层分类优化提取仿真  

Big Data Center Storage Information Hierarchical Classification Optimization Extraction Simulation

作　　者：王岩[1] WANG Yan(College of Humanities&Information of Changchun University of Technology,Changchun Jilin 130122,China)

机构地区：[1]长春工业大学人文信息学院,吉林长春130122

出　　处：《计算机仿真》2020年第4期406-409,共4页Computer Simulation

基　　金：民办高校教师工作量及津贴管理平台研发吉高学会[2015]7号课题(JGJX2015D338)。

摘　　要：目前信息分类提取方法不能满足用户在大数据时代下的信息获取速度需求,为此,提出了基于大数据中心存储信息分层分类优化的信息提取方法。提取数据信息的特征,对得到的信息特征进行校对和调整,在获得存储机制下大量信息的关键特征后,采用信息校验方法消除冗余信息,在信息的校验过程中获取冗余信息的二维坐标,根据这个坐标进行二次检验,确保冗余信息完全消除。利用获取的信息关键特征系数,对比校验区域信息,完成对信息的精确检测,保证信息分类分层优化的有效性。将优化后的信息作为分层分类信息提取的样本,通过条件假设和似然比对事件的发生概率的计算结果确定事件的发生概率,实现对分层分类优化后信息的提取。仿真结果证明,所提方法在提取大数据中心存储信息时,具有速度快、准确率高、信息损失量低等特点。In this article, a method of information extraction based on the hierarchical classification optimization of storage information in big data center was proposed. At first, the features of data information were extracted. And then, information features were proofread and adjusted. After the key features of massive information under the storage mechanism were obtained, the method of information verification was used to eliminate the redundant information. The two-dimensional coordinate of redundant information was obtained in the process of checking information. According to this coordinate, the secondary check was carried out, so that the redundant information was completely eliminated. In addition, the key feature coefficients of information were used to compare and verify the regional information, so as to complete the accuracy test for information. Thus, the effectiveness of hierarchical classification optimization of information could be ensured. Moreover, the optimized information was taken as the sample of extracting the hierarchical classification information. Finally, the probability of event occurrence was determined by calculating the probability of condition assumption and likelihood rate, and then the information extraction after hierarchical classification optimization was achieved. Simulation results show that the proposed method has the advantages of high speed, high accuracy and low loss of information in extracting the storage information in big data center.

关 键 词：大数据中心 存储信息 分层分类 优化 提取 

分 类 号：TP317[自动化与计算机技术—计算机软件与理论]