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Temporal conditions and integrity constraints in active database systems
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Data structures for mobile data
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
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Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Indexing moving points (extended abstract)
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Indexing the positions of continuously moving objects
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
A foundation for representing and querying moving objects
ACM Transactions on Database Systems (TODS)
Maintaining approximate extent measures of moving points
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
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SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Modeling and Querying Moving Objects
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
Journal of Computer and System Sciences - Special issue on PODS 2000
STRIPES: an efficient index for predicted trajectories
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Approximating extent measures of points
Journal of the ACM (JACM)
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Computational Geometry: Theory and Applications - Special issue on the 18th annual symposium on computational geometrySoCG2002
Indexing the Trajectories of Moving Objects in Networks*
Geoinformatica
Indexing mobile objects using dual transformations
The VLDB Journal — The International Journal on Very Large Data Bases
Smooth kinetic maintenance of clusters
Computational Geometry: Theory and Applications - Special issue on the 19th annual symposium on computational geometry - SoCG 2003
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ACM Transactions on Database Systems (TODS)
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ACM Transactions on Database Systems (TODS)
On past-time indexing of moving objects
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Pervasive and Mobile Computing
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VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
A scalable constraint-based Q-hash indexing for moving objects
Information Sciences: an International Journal
AIRSTD: An Approach for Indexing and Retrieving Spatio-Temporal Data
Advanced Internet Based Systems and Applications
The RUM-tree: supporting frequent updates in R-trees using memos
The VLDB Journal — The International Journal on Very Large Data Bases
Smooth kinetic maintenance of clusters
Computational Geometry: Theory and Applications - Special issue on the 19th annual symposium on computational geometry - SoCG 2003
Location-dependent query processing: Where we are and where we are heading
ACM Computing Surveys (CSUR)
Continuous online index tuning in moving object databases
ACM Transactions on Database Systems (TODS)
Using compressed index structures for processing moving objects in large spatio-temporal databases
Journal of Systems and Software
The COST benchmark—comparison and evaluation of spatio-temporal indexes
DASFAA'06 Proceedings of the 11th international conference on Database Systems for Advanced Applications
International Journal of Intelligent Information and Database Systems
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We present a new technique called STAR-tree, based on R*- tree, for indexing a set of moving points so that various queries, including range queries, time-slice queries, and nearest-neighbor queries, can be answered efficiently. A novel feature of the index is that it is self-adjusting in the sense that it re-organizes itself locally whenever its query performance deteriorates. The index provides tradeoffs between storage and query performance and between time spent in updating the index and in answering queries. We present detailed performance studies and compare our methods with the existing ones under a varying type of data sets and queries. Our experiments show that the index proposed here performs considerably better than the previously known ones.