南京大学学报(自然科学版) ›› 2018, Vol. 54 ›› Issue (1): 97–.
杨 宇1，吉根林1*，赵 斌1，黄潇婷2
Yang Yu1，Ji Genlin1*，Zhao Bin1，Huang Xiaoting2
摘要： 现有移动对象聚集模式因为模式定义的不足，无法全面地反映移动对象群体聚集运动．提出一种新的移动对象聚集模式，称为汇合模式，该模式从移动对象群体运动形态出发设计，准确反映群体的变化趋势，有效识别群体聚集运动．汇合模式挖掘过程中使用簇包含关系保证群体之间的关联性，识别群体变化趋势．通过相邻时刻的簇集合进行条件为簇包含的连接操作，实现汇合模式的挖掘．利用移动对象簇之间的空间关系对连接操作进行剪枝，提升汇合模式挖掘的效率．针对汇合模式挖掘中移动对象聚类效率较低的问题，使用四叉树改进DBSCAN(Density－Based Spatial Clustering of Applications with Noise)聚类算法，进一步提升了汇合模式挖掘算法的性能．利用真实的GPS轨迹数据进行实验，结果表明汇合模式挖掘方法是有效的．
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