On generating all maximal independent sets
Information Processing Letters
Counting classes are at least as hard as the polynomial-time hierarchy
SIAM Journal on Computing
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
A probabilistic relational model and algebra
ACM Transactions on Database Systems (TODS)
Integrating information by outerjoins and full disjunctions (extended abstract)
PODS '96 Proceedings of the fifteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
A probabilistic relational algebra for the integration of information retrieval and database systems
ACM Transactions on Information Systems (TOIS)
ProbView: a flexible probabilistic database system
ACM Transactions on Database Systems (TODS)
On the Equivalence of Database Models
Journal of the ACM (JACM)
On the Desirability of Acyclic Database Schemes
Journal of the ACM (JACM)
Degrees of acyclicity for hypergraphs and relational database schemes
Journal of the ACM (JACM)
The Management of Probabilistic Data
IEEE Transactions on Knowledge and Data Engineering
The Theory of Probabilistic Databases
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
An incremental algorithm for computing ranked full disjunctions
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Full disjunctions: polynomial-delay iterators in action
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
An incremental algorithm for computing ranked full disjunctions
Journal of Computer and System Sciences
ProTDB: probabilistic data in XML
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
An abstract framework for generating maximal answers to queries
ICDT'05 Proceedings of the 10th international conference on Database Theory
Asymptotic conditional probabilities for conjunctive queries
ICDT'05 Proceedings of the 10th international conference on Database Theory
Matching twigs in probabilistic XML
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Efficiently enumerating results of keyword search over data graphs
Information Systems
MCDB: a monte carlo approach to managing uncertain data
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Query efficiency in probabilistic XML models
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
Incorporating constraints in probabilistic XML
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Generating all maximal induced subgraphs for hereditary and connected-hereditary graph properties
Journal of Computer and System Sciences
Generating efficient safe query plans for probabilistic databases
Data & Knowledge Engineering
Modeling and querying probabilistic XML data
ACM SIGMOD Record
Incorporating constraints in probabilistic XML
ACM Transactions on Database Systems (TODS)
Proceedings of the 13th International Conference on Database Theory
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
ADBIS'10 Proceedings of the 14th east European conference on Advances in databases and information systems
Combining intensional with extensional query evaluation in tuple independent probabilistic databases
Information Sciences: an International Journal
Proceedings of the VLDB Endowment
Journal of the ACM (JACM)
Aggregate queries on probabilistic record linkages
Proceedings of the 15th International Conference on Extending Database Technology
An embedded co-processor for accelerating window joins over uncertain data streams
Microprocessors & Microsystems
The complexity of mining maximal frequent subgraphs
Proceedings of the 32nd symposium on Principles of database systems
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Conceptually, the common approach to manipulating probabilistic data is to evaluate relational queries and then calculate the probability of each tuple in the result. This approach ignores the possibility that the probabilities of complete answers are too low and, hence, partial answers (with sufficiently high probabilities) become important. Therefore, we consider the semantics in which answers are maximal (i.e., have the smallest degree of incompleteness), subject tothe constraint that the probability is still above a given threshold. We investigate the complexity of joining relations under the above semantics. In contrast to the deterministic case, this approach gives rise to two different enumeration problems. The first is finding all maximal sets of tuples that are join consistent, connected and have a joint probability above the threshold. The second is computing all maximal tuples that are answers of partial joins and have a probability above the threshold. Both problems are tractable under data complexity. We also consider query-and-data complexity, which rules out as efficient the following naive algorithm: compute all partial answers and then choose the maximal ones among those with probabilities above the threshold. We give efficient algorithms for several, important special cases. We also show that, in general, the first problem is NP-hard whereas the secondis #P-hard.