Direct transitive closure algorithms: design and performance evaluation
ACM Transactions on Database Systems (TODS)
A performance study of transitive closure algorithms
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Introduction to Algorithms
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Fast Computation of Sparse Datacubes
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
On the Computation of Multidimensional Aggregates
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Evaluating probabilistic queries over imprecise data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
OLAP over uncertain and imprecise data
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Efficient query evaluation on probabilistic databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Management of probabilistic data: foundations and challenges
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Estimating statistical aggregates on probabilistic data streams
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
OLAP over imprecise data with domain constraints
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Supporting OLAP operations over imperfectly integrated taxonomies
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Query answering techniques on uncertain and probabilistic data: tutorial summary
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Estimating statistical aggregates on probabilistic data streams
ACM Transactions on Database Systems (TODS)
Systems aspects of probabilistic data management
Proceedings of the VLDB Endowment
Probabilistic databases: diamonds in the dirt
Communications of the ACM - Barbara Liskov: ACM's A.M. Turing Award Winner
Privacy-Preserving Data Publishing
Foundations and Trends in Databases
ADBIS'10 Proceedings of the 14th east European conference on Advances in databases and information systems
Aggregate queries on probabilistic record linkages
Proceedings of the 15th International Conference on Extending Database Technology
P-top-k queries in a probabilistic framework from information extraction models
Computers & Mathematics with Applications
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Recent work proposed extending the OLAP data model to support data ambiguity, specifically imprecision and uncertainty. A process called allocation was proposed to transform a given imprecise fact table into a form, called the Extended Database, that can be readily used to answer OLAP aggregation queries.In this work, we present scalable, efficient algorithms for creating the Extended Database (i.e., performing allocation) for a given imprecise fact table. Many allocation policies require multiple iterations over the imprecise fact table, and the straightforward evaluation approaches introduced earlier can be highly inefficient. Optimizing iterative allocation policies for large datasets presents novel challenges, and has not been considered previously to the best of our knowledge. In addition to developing scalable allocation algorithms, we present a performance evaluation that demonstrates their efficiency and compares their performance with respect to straight-foward approaches.