Research And Application Of Government Affairs Information System Based On Multisource Data

The Internet is ubiquitous in our lives.With the rapid development of the Internet,we have gradually entered the era of "data explosion".In the past two years,we have produced more than 90%of the total amount of data all over the world.This considerable amount of data also means a variety of data sources.Effectively acquiring,integrating and analyzing multi-source heterogeneous big data can be a powerful tool for solving problems encountered in people's lives.This is not only an opportunity but also a challenge for both researchers and incorporations.Since 2015,China's "Internet+Government" fashion has developed rapidly.While the government departments are actively investing in self-built government applications,the "Internet + government" services built on third-party platforms is also developing rapidly.Therefore,it is of great resear^ch value to combine information technology with practical application and to build a government information system relying on multi-source data to solve the problems encountered in urban construction and government services.The research topic of this thesis is the research and application of government information system based on multi-source data.This thesis first expounds the overall structure and module structure of the government information system,introduces the main functions and research focus of each part,and provides the technical basis for the later research content.In the study of the management of floating population,we focus on the suspicious personnel identification algorithm based on machine learning,and build an information management platform based on multi-source public security data.In the research of invoice classification code recognition problem,we extract the text feature of commodity from the massive invoice data,realize the classification and coding identification of the invoice based on the naive Bayesian algorithm,and construct a high-performance classification coding m odel training module and prediction service.In the research of urban functional area identification based on mobile big data,we explored the problem of identifying urban functional areas based on traffic data based on clustering algorithm.Finally,we summarize the research results of the proj ect and introduce possible future research.