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Research On Social Security Decision-making Information Service Based On GIS

Posted on:2015-07-26Degree:MasterType:Thesis
Country:ChinaCandidate:D ChenFull Text:PDF
GTID:2308330461474636Subject:Information management and information systems
Abstract/Summary:PDF Full Text Request
The research on application of geographic information system (GIS) in the e-government of China is extensive and sustained. Currently, with the function of GIS itself or combined use with other technologies, the application of GIS in e-government is mainly to provide various government information services by taking the spatial information as a carrier. Thereof, providing decision-making support relying on the spatial orientation, spatial analysis and visualization function of GIS has demonstrated a significant performance. However, the most use of GIS at present is confined to specific departments, such as the surveying and mapping, land resources planning, city construction, weather forecast and other fields which own obvious spatial features. The decision-making information service based on GIS has not been popularized in the government sectors.In this paper, on the basis of analyzing the obvious spatial features of transaction information involved in the social security decision-making, the author proposed that taking the application of GIS in e-government to a specific government sector-social security department. The main work of this paper is as follows:(i) Taking the opportunity of GIS application in the e-government field, the author firstly reviewed the development status of GIS application in government decision-making and discussed the social security department’s requirements on decision-making technologies. Then the author proposed that the GIS technology can be infiltrated into the social security department’s decision-making. Also, the limitation for GIS to serve for the social security decision-making as a single technology was discussed, thus to lead to the data mining technology and the realization of the integrated application of GIS and data mining in the social security decision-making. Based on the existing research foundation, a loosely coupled mode for the integration of GIS and data mining was adopted, and a social security decision-oriented GIS spatial e-government data mining model was designed on this basis,(ii) The attribute and spatial data pretreatment technology on the e-government spatial data mining preparation stage were discussed as an emphasis, and a spatial data pretreatment process specific to the social security e-government was designed. The pretreatment of attribute data in the GIS database mainly involves discretization and concept hierarchy, and that of spatial data involves the spatial relationship and the calculation of the corresponding spatial predicate. Also, a spatial predicate connection table shall be established to realize the real integration of attribute data and spatial data, which will be convenient for handling the spatial data to discover the spatial knowledge by using general data mining methods.(iii) Under the designed GIS spatial e-government data mining model, two concrete spatial e-government data mining ideas were discussed, i.e., e-government spatial characteristic rules mining and e-government spatial association rules mining. Through collecting the map data and attribute data related to the social security business, a GIS spatial database for social security was established. Then, aiming at concrete decision problems, the author realized the two spatial e-government data mining ideas by the combined using of ArcGIS and SPSS Clementine platform. The analysis on the data mining results has proved the feasibility and effectiveness of the integrated application of GIS and data mining technologies in the social security decision-making. Finally, the countermeasure and suggestions for advancing the GIS platform integrated with the data mining technology in the social security department were proposed.
Keywords/Search Tags:Social Security Decision-Making, Geographic Information System (GIS), Data Mining, Spatial Predicate, Association Rules
PDF Full Text Request
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