Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
Updating and Querying Databases that Track Mobile Units
Distributed and Parallel Databases - Special issue on mobile data management and applications
Data Management in Location-Dependent Information Services
IEEE Pervasive Computing
Location Privacy in Pervasive Computing
IEEE Pervasive Computing
Evaluating probabilistic queries over imprecise data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Cover story: they know where you are
IEEE Spectrum
The D-Tree: An Index Structure for Planar Point Queries in Location-Based Wireless Services
IEEE Transactions on Knowledge and Data Engineering
Proactive Caching for Spatial Queries in Mobile Environments
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Location-Dependent Queries in Mobile Contexts: Distributed Processing Using Mobile Agents
IEEE Transactions on Mobile Computing
Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking
Proceedings of the 1st international conference on Mobile systems, applications and services
Continuous nearest neighbor search
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Efficient indexing methods for probabilistic threshold queries over uncertain data
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Uncertain distance-based range queries over uncertain moving objects
Journal of Computer Science and Technology
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Location-Based Spatial Queries (LBSQ) are becoming more and more useful in location-based services such as those provided by cell-phones, Wireless LAN and GPS technologies. They support the access to information resources by taking into account the spatial context of the user when submitting the query, and the spatial location of the searched resources (instances). In fact, in a LBSQ the key-selection condition is generally a constraint on the distance of the resources in the database (instances) from the user location. One deficiency of current approaches is the fact that they do not manage the uncertainty that often characterizes the knowledge of either the user location or the searched instances. A model for representing and evaluating uncertain Location-Based Spatial Queries is proposed in which besides location uncertainty also the spatial condition can be imprecise. A two-step evaluation procedure of LBSQs is outlined based on a filter and on a refinement phase.