An introduction to splines for use in computer graphics & geometric modeling
An introduction to splines for use in computer graphics & geometric modeling
ACM Transactions on Database Systems (TODS)
Linear clustering of objects with multiple attributes
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Towards an analysis of range query performance in spatial data structures
PODS '93 Proceedings of the twelfth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
CIKM '93 Proceedings of the second international conference on Information and knowledge management
Multi-step processing of spatial joins
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Spatio-temporal composition and indexing for large multimedia applications
Multimedia Systems
Overlapping linear quadtrees: a spatio-temporal access method
Proceedings of the 6th ACM international symposium on Advances in geographic information systems
Mobile Computing and Databases-A Survey
IEEE Transactions on Knowledge and Data Engineering
Analysis of the Clustering Properties of the Hilbert Space-Filling Curve
IEEE Transactions on Knowledge and Data Engineering
The Effect of Buffering on the Performance of R-Trees
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Novel Approaches in Query Processing for Moving Object Trajectories
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Multiple Range Query Optimization in Spatial Databases
ADBIS '98 Proceedings of the Second East European Symposium on Advances in Databases and Information Systems
Capturing the Uncertainty of Moving-Object Representations
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
DynaMark: A Benchmark for Dynamic Spatial Indexing
MDM '03 Proceedings of the 4th International Conference on Mobile Data Management
High-performance spatial indexing for location-based services
WWW '03 Proceedings of the 12th international conference on World Wide Web
Evaluating probabilistic queries over imprecise data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Querying Imprecise Data in Moving Object Environments
IEEE Transactions on Knowledge and Data Engineering
Indexing the Trajectories of Moving Objects in Networks*
Geoinformatica
A spatiotemporal uncertainty model of degree 1.5 for continuously changing data objects
Proceedings of the 2006 ACM symposium on Applied computing
Buddy tracking - efficient proximity detection among mobile friends
Pervasive and Mobile Computing
The tornado model: uncertainty model for continuously changing data
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Interpolating and using most likely trajectories in moving-objects databases
DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
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Position data is expected to play a central role in a wide range of mobile computing applications, including advertising, leisure, safety, security, tourist, and traffic applications. Applications such as these are characterized by large quantities of wirelessly Internet-worked, position-aware mobile objects that receive services where the objects' position is essential. The movement of an object is captured via sampling, resulting in a trajectory consisting of a sequence of connected line segments for each moving object. This paper presents a technique for querying these trajectories. The technique uses indices for the processing of spatiotemporal range queries on trajectories. If object movement is constrained by the presence of infrastructure, e.g., lakes, park areas, etc., the technique is capable of exploiting this to reduce the range query, the purpose being to obtain better query performance. Specifically, an algorithm is proposed that segments the original range query based on the infrastructure contained in its range. The applicability and limitations of the proposal are assessed via empirical performance studies with varying datasets and parameter settings.