A model for the prediction of R-tree performance
PODS '96 Proceedings of the fifteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Dimensionality reduction for similarity searching in dynamic databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
The onion technique: indexing for linear optimization queries
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Optimal aggregation algorithms for middleware
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
PREFER: a system for the efficient execution of multi-parametric ranked queries
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Progressive approximate aggregate queries with a multi-resolution tree structure
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
Evaluating probabilistic queries over imprecise data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
GADT: A Probability Space ADT for Representing and Querying the Physical World
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Querying Imprecise Data in Moving Object Environments
IEEE Transactions on Knowledge and Data Engineering
Supporting top-k join queries in relational databases
The VLDB Journal — The International Journal on Very Large Data Bases
RankSQL: query algebra and optimization for relational top-k queries
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
U-DBMS: a database system for managing constantly-evolving data
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Approximate Processing of Massive Continuous Quantile Queries over High-Speed Data Streams
IEEE Transactions on Knowledge and Data Engineering
Answering top-k queries using views
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
The new Casper: query processing for location services without compromising privacy
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
ULDBs: databases with uncertainty and lineage
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Branch-and-bound processing of ranked queries
Information Systems
Probabilistic skylines on uncertain data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Time series compressibility and privacy
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Enabling data retrieval: by ranking and beyond
Enabling data retrieval: by ranking and beyond
Monochromatic and bichromatic reverse skyline search over uncertain databases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Ranking queries on uncertain data: a probabilistic threshold approach
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Probabilistic nearest-neighbor query on uncertain objects
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Probabilistic similarity join on uncertain data
DASFAA'06 Proceedings of the 11th international conference on Database Systems for Advanced Applications
Finding the least influenced set in uncertain databases
Information Systems
Similarity search and mining in uncertain databases
Proceedings of the VLDB Endowment
Probabilistic inverse ranking queries in uncertain databases
The VLDB Journal — The International Journal on Very Large Data Bases
Efficient probabilistic reverse nearest neighbor query processing on uncertain data
Proceedings of the VLDB Endowment
Continuous inverse ranking queries in uncertain streams
SSDBM'11 Proceedings of the 23rd international conference on Scientific and statistical database management
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Query processing in the uncertain database has become increasingly important due to the wide existence of uncertain data in many real applications. Different from handling precise data, the uncertain query processing needs to consider the data uncertainty and answer queries with confidence guarantees. In this paper, we formulate and tackle an important query, namely probabilistic inverse ranking (PIR) query, which retrieves possible ranks of a given query object in an uncertain database with confidence above a probability threshold. We present effective pruning methods to reduce the PIR search space, which can be seamlessly integrated into an efficient query procedure. Furthermore, we also tackle the problem of PIR query processing in high dimensional spaces, which reduces high dimensional uncertain data to a lower dimensional space. The proposed reduction technique may shed light on processing high dimensional uncertain data for other query types. Extensive experiments have demonstrated the efficiency and effectiveness of our proposed approaches over both real and synthetic data sets, under various experimental settings.