The design and analysis of spatial data structures
The design and analysis of spatial data structures
Cutting hyperplanes for divide-and-conquer
Discrete & Computational Geometry
The exact fitting problem in higher dimensions
Computational Geometry: Theory and Applications
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
New Lower Bounds for Convex Hull Problems in Odd Dimensions
SIAM Journal on Computing
Introduction to Algorithms
Analyzing Relative Motion within Groups of Trackable Moving Point Objects
GIScience '02 Proceedings of the Second International Conference on Geographic Information Science
Discovering Similar Multidimensional Trajectories
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Geographic Data Mining and Knowledge Discovery
Geographic Data Mining and Knowledge Discovery
Time-focused clustering of trajectories of moving objects
Journal of Intelligent Information Systems
Dimensionality reduction for long duration and complex spatio-temporal queries
Proceedings of the 2007 ACM symposium on Applied computing
Discovering personally meaningful places: An interactive clustering approach
ACM Transactions on Information Systems (TOIS)
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
Evolution of clusters in dynamic point patterns: with a case study of Ants' simulation
International Journal of Geographical Information Science
A Problem Oriented Approach to Data Mining in Distributed Spatio-temporal Database
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
Discovery of convoys in trajectory databases
Proceedings of the VLDB Endowment
Composite Spatio-Temporal Co-occurrence Pattern Mining
WASA '08 Proceedings of the Third International Conference on Wireless Algorithms, Systems, and Applications
Towards a taxonomy of movement patterns
Information Visualization
Exploring movement-similarity analysis of moving objects
SIGSPATIAL Special
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)
Spatiotemporal pattern queries
Geoinformatica
SSDBM'11 Proceedings of the 23rd international conference on Scientific and statistical database management
How do people's concepts of place relate to physical locations?
INTERACT'05 Proceedings of the 2005 IFIP TC13 international conference on Human-Computer Interaction
NNCluster: an efficient clustering algorithm for road network trajectories
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part II
Community trend outlier detection using soft temporal pattern mining
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part II
International Journal of Intelligent Information and Database Systems
A framework of traveling companion discovery on trajectory data streams
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
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Moving point object data can be analyzed through the discovery of patterns. We consider the computational efficiency of detecting four such spatio-temporal patterns, namely flock, leadership, convergence, and encounter, as defined by Laube et al., 2004. These patterns are large enough subgroups of the moving point objects that exhibit similar movement in the sense of direction, heading for the same location, and/or proximity. By the use of techniques from computational geometry, including approximation algorithms, we improve the running time bounds of existing algorithms to detect these patterns.