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作 者:邓斌 陈会平 李凯勇[2] DENG Bin;CHEN Hui-ping;LI Kai-yong(School of Electronic Information and Computer Engineering,Sichuan Institute of Industrial Technology,Deyang Sichuan 618500,China;Qinghai Nationalities University Physics and Electronic Information Engineering,Xining Qinghai 810007,China)
机构地区:[1]四川工业科技学院电子信息与计算机工程学院,四川德阳618500 [2]青海民族大学物理与电子信息工程学院,青海西宁810007
出 处:《计算机仿真》2021年第7期371-375,共5页Computer Simulation
基 金:国家级项目:教育部高等教育司关于公布有关企业支持的2019年第一批产学合作协同育人项目立项名单的函(201901075003)。
摘 要:大数据时代下数据查询频率逐渐增多,为提升用户搜寻信息准确性与实时性,提出一种基于元数据关联特征的交互式数据快速查询方法。分析大数据交互式流程,在交互式数据预处理阶段定位异常数据,透明化交互过程,支持数据溯源,让用户理解结果与初始数据相对关系,给用户极佳操作体验;运用Map Reduce编程模型完成元数据操作处理,使用单次扫描方式,并行元数据抽样得到精确元数据关联结果;利用相空间重构方式组建高维相空间,代入F.Takens嵌入理论,获取元数据关联差分累积函数特征,并将元数据关联特征矩阵奇异值分解,完成交互式数据快速查询。仿真结果证明,所提方法的交互式数据查询准确率较高,且提升了数据关联查询效率。A fast query method based on metadata association feature is presented for improving the accuracy and real-time of users’ searching information. The interactive process of big data was analyzed in detail to locate abnormal data, make the interactive process transparent and trace the source of supporting data, so that users can understand the relative relationship between the results and the initial data for supplying users excellent operation experience. Based on the Map Reduce programming model, the operation of metadata was completed. The single scan method was used to parallelize the sampling of metadata, and the accurate results of metadata Association were obtained. According to the reconstruction method of phase space, high dimensional phase space was established, and F. Takens embedding theory was used to obtain the characteristics of metadata association differential cumulative function. Meanwhile, the singular value of the associated characteristic matrix of metadata was decomposed. Eventually, the fast query of interactive data was achieved. The simulation results show that the method has high interactive data query accuracy and improved data association query efficiency.
分 类 号:TP357[自动化与计算机技术—计算机系统结构]
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