A probabilistic relational algebra for the integration of information retrieval and database systems
ACM Transactions on Information Systems (TOIS)
Answering queries using views: A survey
The VLDB Journal — The International Journal on Very Large Data Bases
A formal analysis of information disclosure in data exchange
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Efficient query evaluation on probabilistic databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Probabilities of Sentences about Very Sparse Random Graphs
Random Structures & Algorithms
Answering queries from statistics and probabilistic views
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Checking for k-anonymity violation by views
VLDB '05 Proceedings of the 31st international conference on Very large data bases
From statistical knowledge bases to degrees of belief: an overview
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
On the efficiency of checking perfect privacy
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
ULDBs: databases with uncertainty and lineage
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
A formal analysis of information disclosure in data exchange
Journal of Computer and System Sciences
Magic Sets and their application to data integration
Journal of Computer and System Sciences
Management of probabilistic data: foundations and challenges
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
Management of data with uncertainties
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Matching twigs in probabilistic XML
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Privacy skyline: privacy with multidimensional adversarial knowledge
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Data Privacy for $\mathcal{ALC}$ Knowledge Bases
LFCS '09 Proceedings of the 2009 International Symposium on Logical Foundations of Computer Science
Detecting privacy violations in database publishing using disjoint queries
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Adversarial-knowledge dimensions in data privacy
The VLDB Journal — The International Journal on Very Large Data Bases
General Database Statistics Using Entropy Maximization
DBPL '09 Proceedings of the 12th International Symposium on Database Programming Languages
Privacy-Preserving Data Publishing
Foundations and Trends in Databases
Representing uncertain data: models, properties, and algorithms
The VLDB Journal — The International Journal on Very Large Data Bases
Understanding cardinality estimation using entropy maximization
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Disclosure detection over data streams in database publishing
Proceedings of the 2011 Joint EDBT/ICDT Ph.D. Workshop
Privacy in GLAV information integration
ICDT'07 Proceedings of the 11th international conference on Database Theory
Query evaluation on a database given by a random graph
ICDT'07 Proceedings of the 11th international conference on Database Theory
Understanding cardinality estimation using entropy maximization
ACM Transactions on Database Systems (TODS)
Detecting dependencies in an anonymized dataset
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
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We study the asymptotic probabilities of conjunctive queries on random graphs.We consider a probabilistic model where the expected graph size remains constant independent of the number of vertices. While it has been known that a convergence law holds for conjunctive queries under this model, we focus on the calculation of conditional probabilities. This has direct applications to database problems like query-view security, i.e. evaluating the probability of a sensitive query given the knowledge of a set of published views. We prove that a convergence law holds for conditional probabilities of conjunctive queries and we give a procedure for calculating the conditional probabilities.