The new Casper: query processing for location services without compromising privacy
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Snapshot density queries on location sensors
MobiDE '07 Proceedings of the 6th ACM international workshop on Data engineering for wireless and mobile access
Privacy: preserving trajectory collection
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
Continuous density queries for moving objects
Proceedings of the Seventh ACM International Workshop on Data Engineering for Wireless and Mobile Access
BerlinMOD: a benchmark for moving object databases
The VLDB Journal — The International Journal on Very Large Data Bases
Effective density queries for moving objects in road networks
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
Path prediction and predictive range querying in road network databases
The VLDB Journal — The International Journal on Very Large Data Bases
A system for destination and future route prediction based on trajectory mining
Pervasive and Mobile Computing
Ranking continuous nearest neighbors for uncertain trajectories
The VLDB Journal — The International Journal on Very Large Data Bases
Mining trajectory patterns using hidden Markov models
DaWaK'07 Proceedings of the 9th international conference on Data Warehousing and Knowledge Discovery
Continuous aggregate nearest neighbor queries
Geoinformatica
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Neurocomputing
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Information Systems Frontiers
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Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
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This paper assumes a setting where a population of objects move continuously in the Euclidean plane. The position of each object, modeled as a linear function from time to points, is assumed known. In this setting, the paper studies the querying for dense regions. In particular, the paper defines a particular type of density query with desirable properties and then proceeds to propose an algorithm for the efficient computation of density queries. While the algorithm may exploit any existing index for the current and near-future positions of moving objects, the Bx-tree is used. The paper reports on an extensive empirical study, which elicits the performance properties of the algorithm.