A Review of Data Fusion Techniques for Government Big Data

Abstract

AbstractNowadays, the development of e-government has ushered in the era of big data. Data is playing an increasingly important role in the government’s social management and public services. Government big data refers to various information resources such as documents, forms, or charts generated or obtained by government departments in the process of performing their duties. Government data is large in scale, various sourced, and diverse, so there are some difficulties in how to effectively fuse and analyze the complex government data to gain accurate decisions under the premise of ensuring key information will be preserved and key features will be taken seriously. Starting from the definition of government data, this paper firstly analyzed the meaning and the characteristics of government data, and problems in dealing with government data. Then discussed data fusion framework and techniques for government data in three directions: data level, feature level, and decision level. Finally, summarized existing technology and put forward problems that needed to be studied in the future.KeywordsGovernment big dataData fusionData levelFeature levelDecision level