Predictive Join Processing between Regions and Moving Objects
ADBIS '08 Proceedings of the 12th East European conference on Advances in Databases and Information Systems
Time-Aware Similarity Search: A Metric-Temporal Representation for Complex Data
SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
Spatio-temporal database research at the University of Melbourne
ACM SIGMOD Record
Optimized algorithms for predictive range and KNN queries on moving objects
Information Systems
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Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Determining objects within isochrones in spatial network databases
ADBIS'10 Proceedings of the 14th east European conference on Advances in databases and information systems
Efficient proximity detection among mobile users via self-tuning policies
Proceedings of the VLDB Endowment
Top-k most influential locations selection
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Top-k similarity join over multi-valued objects
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part I
Continuous queries on trajectories of moving objects
Proceedings of the 16th International Database Engineering & Applications Sysmposium
Countering overlapping rectangle privacy attack for moving kNN queries
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Accelerating spatial join operations using bit-indices
ADC '11 Proceedings of the Twenty-Second Australasian Database Conference - Volume 115
A branch and bound method for min-dist location selection queries
ADC '12 Proceedings of the Twenty-Third Australasian Database Conference - Volume 124
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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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The continuous intersection join query is computationally expensive yet important for various applications on moving objects. No previous study has specifically addressed this query type. We can adopt a naive algorithm or extend an existing technique (TP-Join) to process the query. However, they compute the answer for either too long or too short a time interval, which results in either a very large computation cost per object update or too frequent answer updates, respectively. This motivates us to optimize the query processing in the time dimension. In this study, we achieve this optimization by introducing the new concept of time-constrained (TC) processing. Further, TC processing enables a set of effective improvement techniques on traditional intersection join algorithms. With a thorough experimental study, we show that our algorithm outperforms the best adapted existing solution by several orders of magnitude.