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SIGMOD
2005
ACM

Robust and Fast Similarity Search for Moving Object Trajectories

9 years 11 months ago
Robust and Fast Similarity Search for Moving Object Trajectories
An important consideration in similarity-based retrieval of moving object trajectories is the definition of a distance function. The existing distance functions are usually sensitive to noise, shifts and scaling of data that commonly occur due to sensor failures, errors in detection techniques, disturbance signals, and different sampling rates. Cleaning data to eliminate these is not always possible. In this paper, we introduce a novel distance function, Edit Distance on Real sequence (EDR) which is robust against these data imperfections. Analysis and comparison of EDR with other popular distance functions, such as Euclidean distance, Dynamic Time Warping (DTW), Edit distance with Real Penalty (ERP), and Longest Common Subsequences (LCSS), indicate that EDR is more robust than Euclidean distance, DTW and ERP, and it is on average 50% more accurate than LCSS. We also develop three pruning techniques to improve the retrieval efficiency of EDR and show that these techniques can be com...
Lei Chen 0002, M. Tamer Özsu, Vincent Oria
Added 26 Jun 2010
Updated 26 Jun 2010
Type Conference
Year 2005
Where SIGMOD
Authors Lei Chen 0002, M. Tamer Özsu, Vincent Oria
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