Modeling Herds and Their Evolvements from Trajectory Data

被引:0
|
作者
Huang, Yan [1 ]
Chen, Cai
Dong, Pinliang [2 ]
机构
[1] Univ North Texas, Dept Comp Sci, Denton, TX 76203 USA
[2] Univ North Texas, Dept Geog, Denton, TX 76203 USA
来源
关键词
Spatio-temporal Data Mining; Spatial Patterns; Spatial Evolvements; Herd Evolvements;
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
A trajectory is the time-stamped path of a moving entity through space. Given a set of trajectories, this paper proposes new conceptual definitions for a spatio-temporal pattern named Herd and four types of herd evolvements: expand, join, shrink, and leave based on the definition of a related term flock. Herd evolvements are identified through measurements of Precision, Recall, and F-score. A graph-based representation, Herd Interaction Graph, or Herding, for herd evolvements is described and an algorithm to generate the graph is proposed and implemented in a Geographic Information System (CIS) environment. A data generator to simulate herd movements and their interactions is proposed and implemented as well. The results suggest that herds and their interactions can be effectively modeled through the proposed measurements and the herd interaction graph from trajectory data.
引用
收藏
页码:90 / +
页数:3
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