Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Trajectory clustering with mixtures of regression models
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
A general probabilistic framework for clustering individuals and objects
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient Retrieval of Similar Time Sequences Under Time Warping
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Incremental Clustering for Mining in a Data Warehousing Environment
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Discovering Similar Multidimensional Trajectories
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Spatio-Temporal Aggregation Using Sketches
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Discrete & Computational Geometry
Clustering moving objects for spatio-temporal selectivity estimation
ADC '04 Proceedings of the 15th Australasian database conference - Volume 27
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
A partial join approach for mining co-location patterns
Proceedings of the 12th annual ACM international workshop on Geographic information systems
Efficient detection of motion patterns in spatio-temporal data sets
Proceedings of the 12th annual ACM international workshop on Geographic information systems
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Time relaxed spatiotemporal trajectory joins
Proceedings of the 13th annual ACM international workshop on Geographic information systems
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
Mining Frequent Trajectory Patterns for Activity Monitoring Using Radio Frequency Tag Arrays
PERCOM '07 Proceedings of the Fifth IEEE International Conference on Pervasive Computing and Communications
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Supporting frequent updates in R-trees: a bottom-up approach
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Computational Geometry: Theory and Applications
Continuous Clustering of Moving Objects
IEEE Transactions on Knowledge and Data Engineering
Indexing land surface for efficient kNN query
Proceedings of the VLDB Endowment
Discovery of convoys in trajectory databases
Proceedings of the VLDB Endowment
The V*-Diagram: a query-dependent approach to moving KNN queries
Proceedings of the VLDB Endowment
Neighbor-based pattern detection for windows over streaming data
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Continuous Intersection Joins Over Moving Objects
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Continuous monitoring of nearest neighbors on land surface
Proceedings of the VLDB Endowment
Traffic density-based discovery of hot routes in road networks
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
Analysis and evaluation of V*-kNN: an efficient algorithm for moving kNN queries
The VLDB Journal — The International Journal on Very Large Data Bases
Scalable shortest paths browsing on land surface
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
T-drive: driving directions based on taxi trajectories
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Swarm: mining relaxed temporal moving object clusters
Proceedings of the VLDB Endowment
Tru-Alarm: Trustworthiness Analysis of Sensor Networks in Cyber-Physical Systems
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Finding shortest path on land surface
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Driving with knowledge from the physical world
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Retrieving k-nearest neighboring trajectories by a set of point locations
SSTD'11 Proceedings of the 12th international conference on Advances in spatial and temporal databases
Computing with Spatial Trajectories
Computing with Spatial Trajectories
On discovering moving clusters in spatio-temporal data
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
On Discovery of Traveling Companions from Streaming Trajectories
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
Reducing Uncertainty of Low-Sampling-Rate Trajectories
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
A highly optimized algorithm for continuous intersection join queries over moving objects
The VLDB Journal — The International Journal on Very Large Data Bases
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The advance of mobile technologies leads to huge volumes of spatio-temporal data collected in the form of trajectory data streams. In this study, we investigate the problem of discovering object groups that travel together (i.e., traveling companions) from trajectory data streams. Such technique has broad applications in the areas of scientific study, transportation management, and military surveillance. To discover traveling companions, the monitoring system should cluster the objects of each snapshot and intersect the clustering results to retrieve moving-together objects. Since both clustering and intersection steps involve high computational overhead, the key issue of companion discovery is to improve the efficiency of algorithms. We propose the models of closed companion candidates and smart intersection to accelerate data processing. A data structure termed traveling buddy is designed to facilitate scalable and flexible companion discovery from trajectory streams. The traveling buddies are microgroups of objects that are tightly bound together. By only storing the object relationships rather than their spatial coordinates, the buddies can be dynamically maintained along the trajectory stream with low cost. Based on traveling buddies, the system can discover companions without accessing the object details. In addition, we extend the proposed framework to discover companions on more complicated scenarios with spatial and temporal constraints, such as on the road network and battlefield. The proposed methods are evaluated with extensive experiments on both real and synthetic datasets. Experimental results show that our proposed buddy-based approach is an order of magnitude faster than the baselines and achieves higher accuracy in companion discovery.