Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
An algorithm to find all paths between two nodes in a graph
Journal of Computational Physics
A Note on the Complexity of Dijkstra's Algorithm for Graphs with Weighted Vertices
IEEE Transactions on Computers
Efficient Algorithms for Shortest Paths in Sparse Networks
Journal of the ACM (JACM)
Discovering Similar Multidimensional Trajectories
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
A Weight-based Map Matching Method in Moving Objects Databases
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Robust and fast similarity search for moving object trajectories
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
On map-matching vehicle tracking data
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Sampling Trajectory Streams with Spatiotemporal Criteria
SSDBM '06 Proceedings of the 18th International Conference on Scientific and Statistical Database Management
Trajectory clustering: a partition-and-group framework
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
On-line discovery of hot motion paths
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Compressing Moving Object Trajectory in Wireless Sensor Networks
International Journal of Distributed Sensor Networks - Sensor Networks, Ubiquitous and Trustworthy Computing
Searching for similar trajectories in spatial networks
Journal of Systems and Software
Trajectory Compression under Network Constraints
SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
Clustering Trajectories of Moving Objects in an Uncertain World
ICDM '09 Proceedings of the 2009 Ninth IEEE International Conference on Data Mining
Nonmaterialized motion information in transport networks
ICDT'05 Proceedings of the 10th international conference on Database Theory
Direction-preserving trajectory simplification
Proceedings of the VLDB Endowment
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The wide usage of location aware devices, such as GPS-enabled cellphones or PDAs, generates vast volumes of spatiotemporal streams of location data raising management challenges, such as efficient storage and querying. Therefore, compression techniques are inevitable also in the field of moving object databases. Related work is relatively limited and mainly driven by line simplification and data sequence compression techniques. Moreover, due to the (unavoidable) erroneous measurements from GPS devices, the problem of matching the location recordings with the underlying traffic network has recently gained the attention of the research community. So far, the proposed compression techniques have not been designed for network constrained moving objects, while on the other hand, existing map matching algorithms do not take compression aspects into consideration. In this paper, we propose solutions tackling the combined, map matched trajectory compression problem, the efficiency of which is demonstrated through an extensive experimental evaluation on offline and online trajectory data using synthetic and real trajectory datasets.