BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
CURE: an efficient clustering algorithm for large databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Novel Approaches in Query Processing for Moving Object Trajectories
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Efficient and Effective Clustering Methods for Spatial Data Mining
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Similarity Search for Multidimensional Data Sequences
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Discovering Similar Multidimensional Trajectories
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Indexing spatio-temporal trajectories with Chebyshev polynomials
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Time relaxed spatiotemporal trajectory joins
Proceedings of the 13th annual ACM international workshop on Geographic information systems
Closest-Point-of-Approach Join for Moving Object Histories
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
MONIC: modeling and monitoring cluster transitions
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Computing longest duration flocks in trajectory data
GIS '06 Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems
Trajectory clustering: a partition-and-group framework
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
Continuous nearest neighbor search
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Computational Geometry: Theory and Applications
Continuous Clustering of Moving Objects
IEEE Transactions on Knowledge and Data Engineering
Discovery of convoys in trajectory databases
Proceedings of the VLDB Endowment
TraClass: trajectory classification using hierarchical region-based and trajectory-based clustering
Proceedings of the VLDB Endowment
On discovering moving clusters in spatio-temporal data
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
SSDBM'10 Proceedings of the 22nd international conference on Scientific and statistical database management
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks
LOCAR: local compression of alternative routes
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
GEOSO - a geo-social model: from real-world co-occurrences to social connections
DNIS'11 Proceedings of the 7th international conference on Databases in Networked Information Systems
On the spatiotemporal burstiness of terms
Proceedings of the VLDB Endowment
Multiplexing trajectories of moving objects
SSDBM'12 Proceedings of the 24th international conference on Scientific and Statistical Database Management
Detecting pedestrian flocks by fusion of multi-modal sensors in mobile phones
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Mining multi-object spatial-temporal movement patterns
SIGSPATIAL Special
Efficient identification and approximation of k-nearest moving neighbors
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
WADS'13 Proceedings of the 13th international conference on Algorithms and Data Structures
Finding extremal sets on the GPU
Journal of Parallel and Distributed Computing
Hi-index | 0.00 |
With the recent advancements and wide usage of location detection devices, large quantities of data are collected by GPS and cellular technologies in the form of trajectories. While most previous work on trajectory-based queries has concentrated on traditional range, nearest-neighbor and similarity queries, there is an increasing interest in queries that capture the "aggregate" behavior of trajectories as groups. Consider, for example, finding groups of moving objects that move "together", i.e. within a predefined distance to each other, for a certain continuous period of time. Such queries typically arise in surveillance applications, e.g. identify groups of suspicious people, convoys of vehicles, flocks of animals, etc. In this paper we first show that the on-line flock discovery problem is polynomial and then propose a framework and several strategies to discover such patterns in streaming spatio-temporal data. Experiments with real and synthetic trajectorial datasets show that the proposed algorithms are efficient and scalable.