TY - GEN
T1 - A spatio-temporal simulation model for movement data generation
AU - Alberg, D.
AU - Last, M.
AU - Elnekave, S.
PY - 2008/12/1
Y1 - 2008/12/1
N2 - The real-world process of generating a large spatio-temporal data collection presents a very difficult technical problem. First, this process is very expensive, requiring a lot of various high-technology software tools and modern hardware infrastructure (sensors, servers, GPS infrastructure etc.) installations; second, the recorded trajectories sometimes cannot represent any special traffic or movement patterns. The simulation framework introduced in this paper can generate diverse trajectory datasets based on predetermined movement patterns.
AB - The real-world process of generating a large spatio-temporal data collection presents a very difficult technical problem. First, this process is very expensive, requiring a lot of various high-technology software tools and modern hardware infrastructure (sensors, servers, GPS infrastructure etc.) installations; second, the recorded trajectories sometimes cannot represent any special traffic or movement patterns. The simulation framework introduced in this paper can generate diverse trajectory datasets based on predetermined movement patterns.
KW - Movement data generation
KW - Movement patterns
KW - Spatio-temporal simulation model
KW - Trajectory
UR - http://www.scopus.com/inward/record.url?scp=62449151156&partnerID=8YFLogxK
U2 - 10.1109/ICDMW.2008.56
DO - 10.1109/ICDMW.2008.56
M3 - Conference contribution
AN - SCOPUS:62449151156
SN - 9780769535036
T3 - Proceedings - IEEE International Conference on Data Mining Workshops, ICDM Workshops 2008
SP - 320
EP - 325
BT - Proceedings - IEEE International Conference on Data Mining Workshops, ICDM Workshops 2008
T2 - IEEE International Conference on Data Mining Workshops, ICDM Workshops 2008
Y2 - 15 December 2008 through 19 December 2008
ER -