基于位置数据和POI的聚类方法

Clustering Method Based on Location Data and POI

提出了一种基于自适应迭代的空间聚类方法,以探索城市空间设施与人们出行行为的内在关系。基于位置数据和POI,先将微博数据进行格网化,转化为连续的格网数据;再利用自适应迭代的聚类方法和相关性分析探索微博的空间分布和城市公共服务设施的时间活跃度。实验结果表明,微博数据和服务设施之间具有较强的相关性,并从大数据分析角度为城市规划布局的优化提供了辅助决策;但将其应用到实际规划中还有待进一步验证和完善。

An spatial clustering method based on adaptive iteration was proposed,in order to explore the relationship between urban public facilities and people's travel behavior. Combined with microblogs and POIs, the mircoblogs were divided into continuous grid surface data at first. And then, the adaptive iterative clustering method and correlation analysis were used to explore the spatial distribution of microblogs and the temporal activity of urban public facilities. The experimental result shows that there is a strong correlation between microblogs and public facilities. And this study can provide a support for optimizaiton of the layout of urban planning on the view of big data analysis.