计算机工程与应用2018，Vol.54Issue(4)：263-270,8.DOI:10.3778/j.issn.1002-8331.1608-0255
停留点空间聚类在景区热点分析中的应用
Application of stay points spatial clustering in hot scenic spots analysis
摘要
Abstract
With broad applications of all kinds of smart phone APP containing Location Based Services(LBS), a large amount of trajectory data left behind tourists can be collected,and mining hot spots from such data will contribute to intelligent service and emergency management.A clustering-based approach for discovering hot spots in spatial trajectories is proposed.Firstly,the DBSCAN(Density-Based Spatial Clustering of Applications with Noise)algorithm is applied to spa-tial clustering due to its simplicity,robustness against noise and ability to discover clusters of arbitrary shapes.However, DBSCAN is sensitive to its two initial input parameters and it is hard to determine them a priori.This paper presents an improved method to choose DBSCAN parameters automatically according to the data statistics distribution.Experimental results are obtained from two-dimensional artificial data sets,four-dimensional UCI Iris data sets and stay points data sets. The final results show that the improved algorithm gets good results with respect to the original DBSCAN and k-means algo-rithms.Finally,the Getis-Ord Gi*hot spot analysis and mapping based on clustering results are conducted in ArcGIS soft-ware,and the grading heats of different scenic spots are given,which are equivalent to the information held by the tourism management.关键词
停留点/空间聚类/热点分析/DBSCAN算法/轨迹/景区Key words
stay point/spatial clustering/hot spot analysis/Density-Based Spatial Clustering of Applications with Noise (DBSCAN)algorithm/trajectory/scenic spot分类
信息技术与安全科学引用本文复制引用
张文元,谈国新,朱相舟..停留点空间聚类在景区热点分析中的应用[J].计算机工程与应用,2018,54(4):263-270,8.基金项目
国家科技支撑计划课题(No.2012BAH83F00). （No.2012BAH83F00）
