摘要
Abstract
The geographic spatial distribution is complex and varied,and map data updates often rely on fixed cycles and a single data source,making it difficult to fully cover all hotspot access areas,thus resulting in poor real-time performance and low accuracy of map hotspot access data updates.Therefore,an automatic update method for map hotspot access data based on a point of interest(POI)search algorithm was proposed.The method widely collected various POI data and provided a reliable foundation for subsequent analysis through data denoising and data cleaning.Spatial indexes of POI data were con-structed through a k-d-tree structure,and attribute indexes of POI data were built through a Hash index to improve data retrieval and processing efficiency.Density-based spatial clustering algorithm was introduced,and dynamic clustering was performed based on the density of POI data,identifying map hotspot access areas of different sizes and densities,calculating hotspot access data popularity values,continuously detecting changes in hotspot access data,and achieving automatic update of map hotspot access data.The experimental results show that the algorithm can accurately identify urban hotspot access areas and map hotspots,achieve real-time and accurate data updates,and significantly improve the quality and user experi-ence of map services,providing effective technical support for the optimization of geographic information systems.关键词
兴趣点搜索算法/地图热点访问数据/空间索引/属性索引/数据自动更新/基于密度的空间聚类算法Key words
POI search algorithm/map hotspot access data/spatial index/attribute index/automatic data update/density-based spatial clustering algorithm分类
测绘与仪器
