A Framework for Spatial Predictive Query Processing and Visualization

被引:1
|
作者
Hendawi, Abdeltawab M. [1 ,2 ]
Ali, Mohamed [2 ]
Mokbel, Mohamed F. [1 ]
机构
[1] Univ Minnesota, Dept Comp Sci & Engn, Minneapolis, MN 55455 USA
[2] Univ Washington, Inst Technol, Ctr Data Sci, Seattle, WA 98195 USA
关键词
MOVING-OBJECTS;
D O I
10.1109/MDM.2015.79
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This demo presents the Panda system for efficient support of a wide variety of predictive spatio-temporal queries. These queries are widely used in several applications including traffic management, location-based advertising, and store finders. Panda targets long-term query prediction as it relies on adapting a long-term prediction function to: (a) scale up to large number of moving objects, and (b) support predictive queries. Panda does not only aim to predict the query answer, but, it also aims to predict the incoming queries such that parts of the query answer can be precomputed before the query arrival. Panda maintains a tunable threshold that achieves a trade-off between the predictive query response time and the system overhead in precomputing the query answer. Equipped with a Graphical User Interface (GUI), audience can explore the Panda demo through issuing predictive queries over a moving set of objects on a map. In addition, they are able to follow the execution of such queries through an eye on the Panda execution engine.
引用
收藏
页码:327 / 330
页数:4
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