A probabilistic relational algebra for the integration of information retrieval and database systems
ACM Transactions on Information Systems (TOIS)
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
ACM Transactions on Modeling and Computer Simulation (TOMACS)
U-DBMS: a database system for managing constantly-evolving data
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Clean Answers over Dirty Databases: A Probabilistic Approach
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Approximate Data Collection in Sensor Networks using Probabilistic Models
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
MauveDB: supporting model-based user views in database systems
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Creating probabilistic databases from information extraction models
VLDB '06 Proceedings of the 32nd 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
Efficient join processing over uncertain data
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
An Introduction to Copulas (Springer Series in Statistics)
An Introduction to Copulas (Springer Series in Statistics)
Scalable approximate query processing with the DBO engine
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Maximally joining probabilistic data
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Efficient query evaluation on probabilistic databases
The VLDB Journal — The International Journal on Very Large Data Bases
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Probabilistic skylines on uncertain data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Matching twigs in probabilistic XML
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
OLAP over imprecise data with domain constraints
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Materialized views in probabilistic databases: for information exchange and query optimization
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
A Sampling-Based Approach to Information Recovery
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Managing Probabilistic Data with MystiQ: The Can-Do, the Could-Do, and the Can't-Do
SUM '08 Proceedings of the 2nd international conference on Scalable Uncertainty Management
The VLDB Journal — The International Journal on Very Large Data Bases
On Query Algebras for Probabilistic Databases
ACM SIGMOD Record
Probabilistic databases: diamonds in the dirt
Communications of the ACM - Barbara Liskov: ACM's A.M. Turing Award Winner
Uncertainty management in rule-based information extraction systems
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Ranking distributed probabilistic data
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Top-k queries on uncertain data: on score distribution and typical answers
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Secondary-storage confidence computation for conjunctive queries with inequalities
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
E = MC3: managing uncertain enterprise data in a cluster-computing environment
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Representing uncertain data: models, properties, and algorithms
The VLDB Journal — The International Journal on Very Large Data Bases
The trichotomy of HAVING queries on a probabilistic database
The VLDB Journal — The International Journal on Very Large Data Bases
The VLDB Journal — The International Journal on Very Large Data Bases
PrDB: managing and exploiting rich correlations in probabilistic databases
The VLDB Journal — The International Journal on Very Large Data Bases
Probabilistic histograms for probabilistic data
Proceedings of the VLDB Endowment
Bridging the gap between intensional and extensional query evaluation in probabilistic databases
Proceedings of the 13th International Conference on Extending Database Technology
Leveraging spatio-temporal redundancy for RFID data cleansing
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
PODS: a new model and processing algorithms for uncertain data streams
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
GRN model of probabilistic databases: construction, transition and querying
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Consistent query answers in inconsistent probabilistic databases
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Probabilistic string similarity joins
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Evaluation of probabilistic threshold queries in MCDB
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Accelerating probabilistic frequent itemset mining: a model-based approach
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Sampling the repairs of functional dependency violations under hard constraints
Proceedings of the VLDB Endowment
Set similarity join on probabilistic data
Proceedings of the VLDB Endowment
MCDB-R: risk analysis in the database
Proceedings of the VLDB Endowment
Scalable probabilistic databases with factor graphs and MCMC
Proceedings of the VLDB Endowment
A*-tree: a structure for storage and modeling of uncertain multidimensional arrays
Proceedings of the VLDB Endowment
k-nearest neighbors in uncertain graphs
Proceedings of the VLDB Endowment
Read-once functions and query evaluation in probabilistic databases
Proceedings of the VLDB Endowment
Conditioning and aggregating uncertain data streams: going beyond expectations
Proceedings of the VLDB Endowment
Probabilistic inverse ranking queries in uncertain databases
The VLDB Journal — The International Journal on Very Large Data Bases
Tractability in probabilistic databases
Proceedings of the 14th International Conference on Database Theory
Synopses for probabilistic data over large domains
Proceedings of the 14th International Conference on Extending Database Technology
Incrementally maintaining classification using an RDBMS
Proceedings of the VLDB Endowment
Tuffy: scaling up statistical inference in Markov logic networks using an RDBMS
Proceedings of the VLDB Endowment
Coalescing executions for fast uncertainty analysis
Proceedings of the 33rd International Conference on Software Engineering
Efficient query answering in probabilistic RDF graphs
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Hybrid in-database inference for declarative information extraction
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Querying uncertain data with aggregate constraints
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Jigsaw: efficient optimization over uncertain enterprise data
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Sensitivity analysis and explanations for robust query evaluation in probabilistic databases
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Fuzzy prophet: parameter exploration in uncertain enterprise scenarios
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
The monte carlo database system: Stochastic analysis close to the data
ACM Transactions on Database Systems (TODS)
Database foundations for scalable RDF processing
RW'11 Proceedings of the 7th international conference on Reasoning web: semantic technologies for the web of data
Cost-efficient repair in inconsistent probabilistic databases
Proceedings of the 20th ACM international conference on Information and knowledge management
Scrubbing query results from probabilistic databases
Proceedings of the 15th Symposium on International Database Engineering & Applications
Probabilistic techniques for obtaining accurate patient counts in Clinical Data Warehouses
Journal of Biomedical Informatics
Aggregation in probabilistic databases via knowledge compilation
Proceedings of the VLDB Endowment
Declarative platform for data sourcing games
Proceedings of the 21st international conference on World Wide Web
DNIS'11 Proceedings of the 7th international conference on Databases in Networked Information Systems
Efficient subject-oriented evaluating and mining methods for data with schema uncertainty
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I
Towards a unified architecture for in-RDBMS analytics
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Tiresias: the database oracle for how-to queries
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Tiresias: a demonstration of how-to queries
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
H-Tree: a hybrid structure for confidence computation in probabilistic databases
APWeb'12 Proceedings of the 14th Asia-Pacific international conference on Web Technologies and Applications
White box sampling in uncertain data processing enabled by program analysis
Proceedings of the ACM international conference on Object oriented programming systems languages and applications
CLARO: modeling and processing uncertain data streams
The VLDB Journal — The International Journal on Very Large Data Bases
Towards high-throughput gibbs sampling at scale: a study across storage managers
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Query execution timing: taming real-time anytime queries on multicore processors
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Causality and responsibility: probabilistic queries revisited in uncertain databases
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Oblivious bounds on the probability of boolean functions
ACM Transactions on Database Systems (TODS)
Sampling from repairs of conditional functional dependency violations
The VLDB Journal — The International Journal on Very Large Data Bases
Anytime approximation in probabilistic databases
The VLDB Journal — The International Journal on Very Large Data Bases
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To deal with data uncertainty, existing probabilistic database systems augment tuples with attribute-level or tuple-level probability values, which are loaded into the database along with the data itself. This approach can severely limit the system's ability to gracefully handle complex or unforeseen types of uncertainty, and does not permit the uncertainty model to be dynamically parameterized according to the current state of the database. We introduce MCDB, a system for managing uncertain data that is based on a Monte Carlo approach. MCDB represents uncertainty via "VG functions," which are used to pseudorandomly generate realized values for uncertain attributes. VG functions can be parameterized on the results of SQL queries over "parameter tables" that are stored in the database, facilitating what-if analyses. By storing parameters, and not probabilities, and by estimating, rather than exactly computing, the probability distribution over possible query answers, MCDB avoids many of the limitations of prior systems. For example, MCDB can easily handle arbitrary joint probability distributions over discrete or continuous attributes, arbitrarily complex SQL queries, and arbitrary functionals of the query-result distribution such as means, variances, and quantiles. To achieve good performance, MCDB uses novel query processing techniques, executing a query plan exactly once, but over "tuple bundles" instead of ordinary tuples. Experiments indicate that our enhanced functionality can be obtained with acceptable overheads relative to traditional systems.