Space meshing based government affair big data mining method

Abstract

The invention discloses a space meshing-based government affair big data mining method. The method comprises the following steps: determining the size of a space grid according to the space granularity of the data in government affair data sets; dividing the space grid and assigning the data in each data set to the grid as attribute values; and carrying out grid data storage and multi-dimensional data mining by taking a cell grid as a unit. According to the method, the data sets of different types are organized under a uniform time-space dimension, so that the mining of government affair big data in different types is effectively realized, and the depth of the information mining is greatly increased.

Description

technical field [0001] The invention belongs to the technical field of network geographic information system applications, and relates to a big data mining method, in particular to a big data mining method capable of effectively organizing and associating multidimensional data and mining information between various types of government affairs data sets. Background technique [0002] With the advent of the era of big data, how to mine useful information from massive data has become an urgent need for people. Most of the existing big data mining technologies are aimed at a single type of data set, and the mining perspective is narrow. In-depth information mining, for example, when mining government affairs open data, due to the large number of government departments, the perspectives of the fields involved in the data are different, and the organizational forms and storage structures of various data sets are very different, so it is difficult to carry out cross-governmental da...

AI Technical Summary

Problems solved by technology

Most of the existing big data mining technologies are aimed at a single type of data set, and the mining perspective is narrow. In-depth information mining, for example, when mining government affairs open data, due to the large number of government departments, the perspectives of the fields involved in the data are different, and the organizational forms and storage structures of various data sets are very different, so it is difficult to carry out cross-government department data mining. information mining between