基于粒度树和使用关系的大数据价值计算研究

Study on Value Calculation of Big Data Based on Granular Tree and Usage Relationship

文中研究了大数据最基本的核心“价值数值”。首先阐述了对大数据进行粒化的粗糙集方法、基于聚类的方法、商空间法、模糊信息方法和云模型方法等,并按它们的共同特性——“划分”,对大数据进行“粒化”,按划分的粗细在大数据中建立了“粒度树”,在“粒度树”中定义了“粒空间”。然后定义了粒空间与代表项目之间的使用关系,以及不同粒空间的使用关系满足的条件。最后按照在粒空间的使用关系中每个粒及每个粒集合的使用情况,将使用情况分为3种:“正则使用”“必然使用”“相关使用”。取它们的属性及对象的平均值,并圆整到0至100,作为大数据的“正则价值”“必然价值”“相关价值”的数值。给出大数据最基本的核心“价值数值”的有效计算方法,又给出大数据最基本的核心“价值数值”计算在远程医疗、城市管理、高等院校等多个领域的应用实例。

Study the core“data results of value”of big data.Firstly,the rough set method,cluster-based method,quotient space method,fuzzy information method and cloud model method for granulating big data are described.According to their common characteristics—“division”,the big data is“granulated”,and a“granularity tree”is established in the big data according to the size of division.“granular space”is defined in the“granular Tree”.Then it defines the usage relationship between the granular space and the representative project,and the conditions that the usage relationship of different granular spaces meets.Finally,according to the usage of each particle and each particle set in the usage relationship of the particle space,the usage is divided into three types:“regular use”“inevitable use”and“related use”.Take the average value of their attributes and objects and round them to 0~100,as the values of“data results of value”“inevitable value”and“relevant value”of big data.The effective calculation method of the core“data results of value”of big data is given,and the application examples of the core“data results of value”calculation of big data in telemedicine,urban management,universities and other fields are also given.