Query evaluation in probabilistic relational databases
Selected papers from the international workshop on Uncertainty in databases and deductive systems
ProbView: a flexible probabilistic database system
ACM Transactions on Database Systems (TODS)
The Management of Probabilistic Data
IEEE Transactions on Knowledge and Data Engineering
An Algebra for Probabilistic Databases
IEEE Transactions on Knowledge and Data Engineering
The Geometry of Uncertainty in Moving Objects Databases
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
The Theory of Probabilistic Databases
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
A Probabilistic Framework for Vague Queries and Imprecise Information in Databases
VLDB '90 Proceedings of the 16th International Conference on Very Large Data Bases
Finding Geographic Information: Collection-Level Metadata
Geoinformatica
Evaluating probabilistic queries over imprecise data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Indexing of Moving Objects for Location-Based Services
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Multidimensional data modeling for location-based services
The VLDB Journal — The International Journal on Very Large Data Bases
Managing uncertainty in moving objects databases
ACM Transactions on Database Systems (TODS)
Aggregate operators in probabilistic databases
Journal of the ACM (JACM)
Finding corresponding objects when integrating several geo-spatial datasets
Proceedings of the 13th annual ACM international workshop on Geographic information systems
Clean Answers over Dirty Databases: A Probabilistic Approach
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
A nearest neighborhood algebra for probabilistic databases
Intelligent Data Analysis
Object fusion in geographic information systems
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Efficient query evaluation on probabilistic databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Integrating data from maps on the world-wide web
W2GIS'06 Proceedings of the 6th international conference on Web and Wireless Geographical Information Systems
Route Search over Probabilistic Geospatial Data
SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
An interactive approach to route search
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Interactive traffic-aware route search on smartphones
Proceedings of the First ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems
Probabilistic parking queries using aging functions
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
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An uncertain geo-spatial dataset is a collection of geo-spatial objects that do not represent accurately real-world entities. Each object has a confidence value indicating how likely it is for the object to be correct. Uncertain data can be the result of operations such as imprecise integration, incorrect update or inexact querying. A k-route, over an uncertain geo-spatial dataset, is a path that travels through the geo-spatial objects, starting at a given location and stopping after visiting k correct objects. A k-route is considered shortest if the expected length of the route is less than or equal to the expected length of any other k-route that starts at the given location. This paper introduces the problem of finding a shortest k-route over an uncertain dataset. Since the problem is a generalization of the traveling salesman problem, it is unlikely to have an efficient solution, i.e., there is no polynomial-time algorithm that solves the problem (unless P=NP). Hence, in this work we consider heuristics for the problem. Three methods for computing a short k-route are presented. The three methods are compared analytically and experimentally. For these three methods, experiments on both synthetic and realworld data show the tradeoff between the quality of the result (i.e., the expected length of the returned route) and the efficiency of the computation.