Counting classes are at least as hard as the polynomial-time hierarchy
SIAM Journal on Computing
Communications of the ACM
Approximating probabilistic inference in Bayesian belief networks is NP-hard
Artificial Intelligence
Holistic twig joins: optimal XML pattern matching
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
On XML integrity constraints in the presence of DTDs
Journal of the ACM (JACM)
OLD Resolution with Tabulation
Proceedings of the Third International Conference on Logic Programming
ICDT '03 Proceedings of the 9th International Conference on Database Theory
Journal of Computer and System Sciences - Special issue on PODS 2000
Testing XML constraint satisfiability
Electronic Notes in Theoretical Computer Science (ENTCS)
On the complexity of managing probabilistic XML data
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
The dichotomy of conjunctive queries on probabilistic structures
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Maximally joining probabilistic data
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
ProTDB: probabilistic data in XML
VLDB '02 Proceedings of the 28th 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
Matching twigs in probabilistic XML
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Query efficiency in probabilistic XML models
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Efficient evaluation of HAVING queries on a probabilistic database
DBPL'07 Proceedings of the 11th international conference on Database programming languages
Querying and updating probabilistic information in XML
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Query efficiency in probabilistic XML models
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
A compositional framework for complex queries over uncertain data
Proceedings of the 12th International Conference on Database Theory
TOP-K projection queries for probabilistic business processes
Proceedings of the 12th International Conference on Database Theory
Query ranking in probabilistic XML data
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Modeling and querying probabilistic XML data
ACM SIGMOD Record
Running tree automata on probabilistic XML
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
XML with incomplete information: models, properties, and query answering
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Incorporating constraints in probabilistic XML
ACM Transactions on Database Systems (TODS)
On the expressiveness of probabilistic XML models
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
Query evaluation over probabilistic XML
The VLDB Journal — The International Journal on Very Large Data Bases
Aggregate queries for discrete and continuous probabilistic XML
Proceedings of the 13th International Conference on Database Theory
Querying parse trees of stochastic context-free grammars
Proceedings of the 13th International Conference on Database Theory
Proceedings of the 13th International Conference on Database Theory
XML with incomplete information
Journal of the ACM (JACM)
Journal of the ACM (JACM)
Capturing continuous data and answering aggregate queries in probabilistic XML
ACM Transactions on Database Systems (TODS)
Finding optimal probabilistic generators for XML collections
Proceedings of the 15th International Conference on Database Theory
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Constraints are important not just for maintaining data integrity, but also because they capture natural probabilistic dependencies among data items. A probabilistic XML database (PXDB) is the probability sub-space comprising the instances of a p-document that satisfy a set of constraints. In contrast to existing models that can express probabilistic dependencies, it is shown that query evaluation is tractable in PXDBs. The problems of sampling and determining well-definedness (i.e., whether the above subspace is nonempty) are also tractable. Furthermore, queries and constraints can include the aggregate functions count, max, min and ratio. Finally, this approach can be easily extended to allow a probabilistic interpretation of constraints.