文章基本信息

标题：A Self-Adjusting Approach to Identify Hotspots
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作者：Haoying Han ; Xianfan Shu
期刊名称：International Review for Spatial Planning and Sustainable Development
电子版ISSN：2187-3666
出版年度：2017
卷号：5
期号：2
页码：104-112
DOI：10.14246/irspsd.5.2_104
语种：English
出版社：空間計画と持続可能な開発国際学会
摘要：Hotspot identification or detection has been widely used in many fields; however the traditional grid-based approaches may incur some problems when dealing with point database. This article expands on three types of mismatch problems in grid-based approach and suggests a point-based approach may be more suitable. Inspired by the DBSCAN algorithm, a self-adjusting approach is then proposed for hotspot detection which overcomes the weakness of parameter sensitivity shared by most clustering approaches. Finally, the data of commercial points of interest of a city is used for demonstration.
关键词：Hotspot Detection;Self-adjusting Approach;Clustering;DBSCAN