Probabilistic Reverse Nearest Neighbor Queries on Uncertain Data

Authors:
Muhammad Aamir Cheema;Xuemin Lin;Wei Wang;Wenjie Zhang;Jian Pei
Affiliations:
University of New South Wales, Sydney;University of New South Wales, Sydney and NICTA;University of New South Wales, Sydney and NICTA;University of New South Wales, Sydney and NICTA;Simon Fraser Univeristy, Burnaby
Venue:
IEEE Transactions on Knowledge and Data Engineering
Year:
2010

Citing 0
Cited 15

Reverse ranking query over imprecise spatial data

Proceedings of the 1st International Conference and Exhibition on Computing for Geospatial Research & Application
Continuous reverse k nearest neighbor monitoring on moving objects in road networks

Information Systems
Similarity search and mining in uncertain databases

Proceedings of the VLDB Endowment
Efficient probabilistic reverse nearest neighbor query processing on uncertain data

Proceedings of the VLDB Endowment
On some geometric problems of color-spanning sets

FAW-AAIM'11 Proceedings of the 5th joint international frontiers in algorithmics, and 7th international conference on Algorithmic aspects in information and management
k-selection query over uncertain data

DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I
Efficient processing of probabilistic set-containment queries on uncertain set-valued data

Information Sciences: an International Journal
MUD: Mapping-based query processing for high-dimensional uncertain data

Information Sciences: an International Journal
An associative classifier for uncertain datasets

PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Evaluating trajectory queries over imprecise location data

SSDBM'12 Proceedings of the 24th international conference on Scientific and Statistical Database Management
Efficiently processing snapshot and continuous reverse k nearest neighbors queries

The VLDB Journal — The International Journal on Very Large Data Bases
Finding top k most influential spatial facilities over uncertain objects

Proceedings of the 21st ACM international conference on Information and knowledge management
UV-diagram: a voronoi diagram for uncertain spatial databases

The VLDB Journal — The International Journal on Very Large Data Bases
Causality and responsibility: probabilistic queries revisited in uncertain databases

Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
On some geometric problems of color-spanning sets

Journal of Combinatorial Optimization

Quantified Score

Hi-index	0.00

Visualization

Abstract

Uncertain data are inherent in various important applications and reverse nearest neighbor (RNN) query is an important query type for many applications. While many different types of queries have been studied on uncertain data, there is no previous work on answering RNN queries on uncertain data. In this paper, we formalize probabilistic reverse nearest neighbor query that is to retrieve the objects from the uncertain data that have higher probability than a given threshold to be the RNN of an uncertain query object. We develop an efficient algorithm based on various novel pruning approaches that solves the probabilistic RNN queries on multidimensional uncertain data. The experimental results demonstrate that our algorithm is even more efficient than a sampling-based approximate algorithm for most of the cases and is highly scalable.