Symbolic Boolean manipulation with ordered binary-decision diagrams
ACM Computing Surveys (CSUR)
Improving the Variable Ordering of OBDDs Is NP-Complete
IEEE Transactions on Computers
Algebraic decision diagrams and their applications
ICCAD '93 Proceedings of the 1993 IEEE/ACM international conference on Computer-aided design
ProbView: a flexible probabilistic database system
ACM Transactions on Database Systems (TODS)
A differential approach to inference in Bayesian networks
Journal of the ACM (JACM)
Model-driven data acquisition in sensor networks
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
Data integration with uncertainty
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
On probabilistic inference by weighted model counting
Artificial Intelligence
Approximating predicates and expressive queries on probabilistic databases
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Using OBDDs for Efficient Query Evaluation on Probabilistic Databases
SUM '08 Proceedings of the 2nd international conference on Scalable Uncertainty Management
BayesStore: managing large, uncertain data repositories with probabilistic graphical models
Proceedings of the VLDB Endowment
Modeling and Reasoning with Bayesian Networks
Modeling and Reasoning with Bayesian Networks
SPROUT: Lazy vs. Eager Query Plans for Tuple-Independent Probabilistic Databases
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Indexing correlated probabilistic databases
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
On the role of context-specific independence in probabilistic inference
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Compiling Bayesian networks using variable elimination
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Compiling Bayesian networks with local structure
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
PrDB: managing and exploiting rich correlations in probabilistic databases
The VLDB Journal — The International Journal on Very Large Data Bases
Compiling relational Bayesian networks for exact inference
International Journal of Approximate Reasoning
Bridging the gap between intensional and extensional query evaluation in probabilistic databases
Proceedings of the 13th International Conference on Extending Database Technology
Computing query probability with incidence algebras
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Lineage processing over correlated probabilistic databases
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Preprocessing boolean formulae for BDDs in a probabilistic context
JELIA'10 Proceedings of the 12th European conference on Logics in artificial intelligence
Scalable probabilistic databases with factor graphs and MCMC
Proceedings of the VLDB Endowment
Read-once functions and query evaluation in probabilistic databases
Proceedings of the VLDB Endowment
Knowledge compilation meets database theory: compiling queries to decision diagrams
Proceedings of the 14th International Conference on Database Theory
Probabilistic Databases
Context-specific independence in Bayesian networks
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Bucket elimination: a unifying framework for probabilistic inference
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Probabilistic management of OCR data using an RDBMS
Proceedings of the VLDB Endowment
Models for incomplete and probabilistic information
EDBT'06 Proceedings of the 2006 international conference on Current Trends in Database Technology
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While extensive work has been done on evaluating queries over tuple-independent probabilistic databases, query evaluation over correlated data has received much less attention even though the support for correlations is essential for many natural applications of probabilistic databases, e.g., information extraction, data integration, computer vision, etc. In this paper, we develop a novel approach for efficiently evaluating probabilistic queries over correlated databases where correlations are represented using a factor graph, a class of graphical models widely used for capturing correlations and performing statistical inference. Our approach exploits the specific values of the factor parameters and the determinism in the correlations, collectively called local structure, to reduce the complexity of query evaluation. Our framework is based on arithmetic circuits, factorized representations of probability distributions that can exploit such local structure. Traditionally, arithmetic circuits are generated following a compilation process and can not be updated directly. We introduce a generalization of arithmetic circuits, called annotated arithmetic circuits, and a novel algorithm for updating them, which enables us to answer probabilistic queries efficiently. We present a comprehensive experimental analysis and show speed-ups of at least one order of magnitude in many cases.