Title
An Efficient Indexing Technique for Location Prediction of Moving Objects
Abstract
The necessity of the future index is increasing to predict the future location of moving objects promptly for various location-based services. However, the prediction performance of most future indexes is lowered by the heavy load of extensive future trajectory search in long-range future queries, and their index maintenance cost is high due to the frequent update of future trajectories. Thus, this paper proposes the Probability Cell Trajectory-Tree (PCT-Tree), a cell-based future indexing technique for efficient long-range future location prediction. The PCT-Tree reduces the size of index by building the probability of extensive past trajectories in the unit of cell, and predicts reliable future trajectories using information on past trajectories. Therefore, the PCT-Tree can minimize the cost of communication in future trajectory prediction and the cost of index rebuilding for updating future trajectories. Through experiment, we proved the superiority of the PCT-Tree over existing indexing techniques in the performance of long-range future queries.
Year
DOI
Venue
2007
10.1007/978-3-540-74827-4_1
KES (2)
Keywords
Field
DocType
future location,efficient long-range future location,long-range future query,location prediction,future trajectory prediction,cell-based future indexing technique,future index,index maintenance cost,future trajectory,reliable future trajectory,efficient indexing technique,extensive future trajectory search,indexation,cell,probability matrix,location based service
Data mining,Stochastic matrix,Computer science,Search engine indexing,Location prediction,Trajectory
Conference
Volume
ISSN
Citations 
4693
0302-9743
1
PageRank 
References 
Authors
0.37
9
4
Name
Order
Citations
PageRank
Dong-Oh Kim1156.72
Kangjun Lee2112.30
Dong-Suk Hong3103.67
Ki-Joon Han4266.76