TY - GEN
T1 - A Parallel Algorithm for Mining Time Relaxed Gradual Clustering Pattern Based on Spatio-Temporal Trajectories
AU - Sun, Hongyan
AU - Ji, Genlin
AU - Zhao, Bin
AU - Liu, Xintao
PY - 2017/9/6
Y1 - 2017/9/6
N2 - As an important area of spatio-Temporal data mining, time relaxed gradual clustering pattern has been attracting broad attention in recent years. Algorithm PTRGSP is proposed to mining time relaxed gradual clustering pattern from spatio-Temporal trajectory, which is implemented under spark framework. All trajectories are divided into point sets with different timestamps, and such point sets are parallel clustered. After that, clusters of different time intervals are joined in parallel to achieve pattern candidates. Candidates are combined to obtain interesting maximal time relaxed gradual clustering pattern. To improve the efficiency of the algorithm PTRGSP, algorithm PTRGSP-G is presented based on grid index for mining time relaxed gradual clustering pattern. The experiment results on real dataset and synthetic trajectory dataset demonstrate the effectiveness and efficiency of the two algorithms.
AB - As an important area of spatio-Temporal data mining, time relaxed gradual clustering pattern has been attracting broad attention in recent years. Algorithm PTRGSP is proposed to mining time relaxed gradual clustering pattern from spatio-Temporal trajectory, which is implemented under spark framework. All trajectories are divided into point sets with different timestamps, and such point sets are parallel clustered. After that, clusters of different time intervals are joined in parallel to achieve pattern candidates. Candidates are combined to obtain interesting maximal time relaxed gradual clustering pattern. To improve the efficiency of the algorithm PTRGSP, algorithm PTRGSP-G is presented based on grid index for mining time relaxed gradual clustering pattern. The experiment results on real dataset and synthetic trajectory dataset demonstrate the effectiveness and efficiency of the two algorithms.
KW - Parallel data mining
KW - Spatio-Temporal trajectory
KW - Time relaxed gradual clustering pattern
UR - http://www.scopus.com/inward/record.url?scp=85031744668&partnerID=8YFLogxK
U2 - 10.1109/CBD.2017.60
DO - 10.1109/CBD.2017.60
M3 - Conference article published in proceeding or book
AN - SCOPUS:85031744668
T3 - Proceedings - 5th International Conference on Advanced Cloud and Big Data, CBD 2017
SP - 308
EP - 313
BT - Proceedings - 5th International Conference on Advanced Cloud and Big Data, CBD 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Advanced Cloud and Big Data, CBD 2017
Y2 - 13 August 2017 through 16 August 2017
ER -