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Research on distributed spatial analysis service of map interest points

GUO Qingsheng;WANG Yong;LAN Zhenjia;ZHOU Hejie;LIU Jiping;JI Yingying;School of Resource and Environment Science,Wuhan University;Chinese Academy of Surveying and Mapping;Beijing NavInfo Polytron Technologies Inc;  
Aiming at the problem of the application analysis of the mass interest points on the internet map,this paper uses MongoDB to design and build a distributed cluster,and stores these internet interest point data.Then,through the MapReduce mechanism to improve and implement the spatial co-location pattern mining Apriori algorithm which is applicable to the mass of interest point data,and several common spatial distribution eigenvalues calculation methods.Finally,according to the web processing service specification of the open geographic information system association,an experimental system of internet interest point distributed analysis service is designed and implemented.The improved algorithm is superior in data throughput and efficiency,and the computational efficiency is better than traditional spatial analysis tools and traditional Apriori algorithm.
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