Discovering Similar Multidimensional Trajectories
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Mining, indexing, and querying historical spatiotemporal data
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Spatiotemporal Aggregate Computation: A Survey
IEEE Transactions on Knowledge and Data Engineering
Mining Frequent Spatio-Temporal Sequential Patterns
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Time-focused clustering of trajectories of moving objects
Journal of Intelligent Information Systems
Distributed spatio-temporal similarity search
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Mining spatio-temporal patterns in object mobility databases
Data Mining and Knowledge Discovery
STMPE: an efficient movement pattern extraction algorithm for spatio-temporal data mining
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part II
Mining mobile group patterns: a trajectory-based approach
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Similarity in (spatial, temporal and) spatio-temporal datasets
Proceedings of the 15th International Conference on Extending Database Technology
International Journal of Intelligent Information and Database Systems
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In this paper, we present an OLAP framework for trajectories of moving objects. We introduce a new operator GROUP_TRAJECTORIES for group-by operations on trajectories and present three implementation alternatives for computing groups of trajectories for group-by aggregation: group by overlap, group by intersection, and group by overlap and intersection. We also present an interactive OLAP environment for resolution drill-down/roll-up on sets of trajectories and parameter browsing. Using generated and real life moving data sets, we evaluate the performance of our GROUP_TRAJECTORIES operator. An implementation of our new interactive OLAP environment for trajectories can be accessed at http://OLAP-T.cgmlab.org.