Discovery of convoys in trajectory databases
Proceedings of the VLDB Endowment
From trajectories to activities: a spatio-temporal join approach
Proceedings of the 2009 International Workshop on Location Based Social Networks
MoveMine: mining moving object databases
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Swarm: mining relaxed temporal moving object clusters
Proceedings of the VLDB Endowment
MoveMine: Mining moving object data for discovery of animal movement patterns
ACM Transactions on Intelligent Systems and Technology (TIST)
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks
Mining multi-object spatial-temporal movement patterns
SIGSPATIAL Special
Calibrating trajectory data for similarity-based analysis
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Graph-Based approaches to clustering network-constrained trajectory data
NFMCP'12 Proceedings of the First international conference on New Frontiers in Mining Complex Patterns
Efficient identification and approximation of k-nearest moving neighbors
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
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We introduce a convoy query that retrieves all convoys from historical trajectories, each of which consists of a set of objects that travelled closely during a certain time period. Convoy query is useful for many applications such as carpooling and traffic jam analysis, however, limited work has been done in the database community. This study proposes three efficient methods for discovering convoys. The main novelty of our methods is to approximate original trajectories by using line simplification methods and perform the discovery process over the simplified trajectories with bounded errors. Our experimental results confirm the effectiveness and efficiency of our methods.