DocumentCode :
2888770
Title :
Mining Trajectories for Spatio-temporal Analytics
Author :
Songhua Xing ; Xuan Liu ; Qing He ; Hampapur, A.
Author_Institution :
IBM T. J. Watson Res. Center, Yorktown Heights, NY, USA
fYear :
2012
fDate :
10-10 Dec. 2012
Firstpage :
910
Lastpage :
913
Abstract :
Mining high resolution trajectories from moving vehicles can provide insightful analytics and enable location based decision making. In this paper, we introduce a trajectory mining prototype system to generate the trajectory heat map at aggregated level for the online spatial-temporal analytics. The proposed method is scalable and efficient since we develop a mechanism using a small subset of trajectory points to capture all trajectory patterns. We experimentally verified the applicability and scalability of this system with large scale real world dataset.
Keywords :
data mining; decision making; spatiotemporal phenomena; traffic engineering computing; location based decision making; moving vehicle; spatiotemporal analytics; trajectory heat map generation; trajectory mining; trajectory mining prototype system; trajectory pattern; Data mining; Global Positioning System; Heating; Roads; Scalability; Trajectory; Vehicles; Spatio-temporal analytics; Trajectory mining; Transit point;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining Workshops (ICDMW), 2012 IEEE 12th International Conference on
Conference_Location :
Brussels
Print_ISBN :
978-1-4673-5164-5
Type :
conf
DOI :
10.1109/ICDMW.2012.25
Filename :
6406543
Link To Document :
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