The power of geometric duality
BIT - Ellis Horwood series in artificial intelligence
The input/output complexity of sorting and related problems
Communications of the ACM
Applications of random sampling in computational geometry, II
Discrete & Computational Geometry - Selected papers from the fourth ACM symposium on computational geometry, Univ. of Illinois, Urbana-Champaign, June 6 8, 1988
Simplex range reporting on a pointer machine
Computational Geometry: Theory and Applications
Efficient searching with linear constraints
Journal of Computer and System Sciences - Special issue on the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on principles of database systems
Foundations of Multidimensional and Metric Data Structures (The Morgan Kaufmann Series in Computer Graphics and Geometric Modeling)
Indexing multi-dimensional uncertain data with arbitrary probability density functions
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Trio: a system for data, uncertainty, and lineage
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
On approximate halfspace range counting and relative epsilon-approximations
SCG '07 Proceedings of the twenty-third annual symposium on Computational geometry
Range search on multidimensional uncertain data
ACM Transactions on Database Systems (TODS)
Efficient query evaluation on probabilistic databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
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
Efficient Evaluation of Probabilistic Advanced Spatial Queries on Existentially Uncertain Data
IEEE Transactions on Knowledge and Data Engineering
Improved bounds and new techniques for Davenport--Schinzel sequences and their generalizations
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Optimal halfspace range reporting in three dimensions
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Threshold query optimization for uncertain data
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Identifying interesting instances for probabilistic skylines
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
Combining intensional with extensional query evaluation in tuple independent probabilistic databases
Information Sciences: an International Journal
UPI: a primary index for uncertain databases
Proceedings of the VLDB Endowment
Efficient and effective similarity search over probabilistic data based on earth mover's distance
Proceedings of the VLDB Endowment
Closest pair and the post office problem for stochastic points
WADS'11 Proceedings of the 12th international conference on Algorithms and data structures
Nearest-neighbor searching under uncertainty
PODS '12 Proceedings of the 31st symposium on Principles of Database Systems
DuoWave: Mitigating the curse of dimensionality for uncertain data
Data & Knowledge Engineering
Effectively indexing the multi-dimensional uncertain objects for range searching
Proceedings of the 15th International Conference on Extending Database Technology
Stabbing horizontal segments with vertical rays
Proceedings of the twenty-eighth annual symposium on Computational geometry
Nearest Neighbor-Based Classification of Uncertain Data
ACM Transactions on Knowledge Discovery from Data (TKDD)
Range counting coresets for uncertain data
Proceedings of the twenty-ninth annual symposium on Computational geometry
Closest pair and the post office problem for stochastic points
Computational Geometry: Theory and Applications
Aggregate nearest neighbor queries in uncertain graphs
World Wide Web
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Querying uncertain data has emerged as an important problem in data management due to the imprecise nature of many measurement data. In this paper we study answering range queries over uncertain data. Specifically, we are given a collection P of n points in R, each represented by its one-dimensional probability density function (pdf). The goal is to build an index on P such that given a query interval I and a probability threshold τ, we can quickly report all points of P that lie in I with probability at least τ. We present various indexing schemes with linear or near-linear space and logarithmic query time. Our schemes support pdf's that are either histograms or more complex ones such as Gaussian or piecewise algebraic. They also extend to the external memory model in which the goal is to minimize the number of disk accesses when querying the index.