基于数据结构编码的国民经济行业分类在舆情监测项目中的应用

Application of National Economy Industry Classification Based on Data Structure Coding in Public Opinion Monitoring Project

GB/T 4754-2017《国民经济行业分类》的代码编制方法为基于整数数字顺序编码,在金融工程的舆情监测项目中进行数据挖掘、机器学习时存在编码数量扩展、层级扩展、属性扩展等问题。根据国民经济行业分类的差别化整数数字顺序编码方式,提出一套基于数据结构的分类编码方法,进而提出采用CSV、XML格式文件进行存储和读取,在舆情监测项目中采用C++语言编制针对CSV格式文件的国民经济行业分类编码的读取程序,并形成XML树状结构。采用基于数据结构的编码方式,具有良好的扩展性,可有效实现编码层级扩展、编码数量扩展、编码属性扩展,能广泛用于数据存储、读写、交换,具有较好的通用性,对于些国民经济统计、分类、存储及金融工程的数据挖掘、机器学习等项目具有借鉴意义。

The coding method of Industrial Classification for National Economic Activities(GB/T 47542017)is based on integer digital sequential coding.When data mining and machine learning are carried out in public opinion monitoring projects of financial engineering,there are some problems,such as coding quantity extension,coding level extension and coding attribute extension.According to the differentiated integer digital sequential coding method of industrial classification for national economic activities,a set of classification and coding method based on data organization is proposed,and then CSV and XML format files are used for storage and reading.In the public opinion monitoring project,C++programming language is used to compile the reading program of industrial classification and coding of national economic activities in CSV format file,and an XML tree structure is formed.The coding method based on data organization has good expansibility,which can effectively realize the coding level expansion,coding quantity expansion and coding attribute expansion.It can be widely used in data storage,reading,writing and exchange,and has good universality.It can be used for reference in some projects of national economic statistics,classification,storage and financial engineering,such as data mining,machine learning and so on.