A Quadtree-based Hierarchical Clustering Method for Visualizing Large Point Dataset

被引：0

作者：

Cai, Qing ^{[1
]}

Zhou, Yimin ^{[1
]}

机构：

[1] Univ Shanghai Sci & Technol, Sch Opt Elect & Comp Engn, Shanghai 200093, Peoples R China

来源：

2016 SIXTH INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND TECHNOLOGY (ICIST) | 2016年

关键词：

Geovisualization; hierarchical clustering; quadtree spatial index; big data;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Many digital map applications have the need to present large quantities of precise point data on the map. Such data can be PM2.5 value, weather information, population in towns, etc. With the development of Internet of Things, we expect such data will grow at a rapid pace. How to visualize such magnitude of data on mobile devices and web broswers becomes a problem. This paper describes a method for interactively visualizing such data, using a combination of grid-based clustering and hierarachical clustering, along with quadtree spatial indexing.

引用

页码：372 / 375

页数：4

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