Conjunctive query answering in probabilistic datalog+/- ontologies
RR'11 Proceedings of the 5th international conference on Web reasoning and rule systems
Answering threshold queries in probabilistic datalog+/-ontologies
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
A landmark-model based system for mining frequent patterns from uncertain data streams
Proceedings of the 15th Symposium on International Database Engineering & Applications
Randomized accuracy-aware program transformations for efficient approximate computations
POPL '12 Proceedings of the 39th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Aggregation in probabilistic databases via knowledge compilation
Proceedings of the VLDB Endowment
Local structure and determinism in probabilistic databases
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
On the complexity of query answering over incomplete XML documents
Proceedings of the 15th International Conference on Database Theory
On the tractability of query compilation and bounded treewidth
Proceedings of the 15th International Conference on Database Theory
Factorised representations of query results: size bounds and readability
Proceedings of the 15th International Conference on Database Theory
DAGger: clustering correlated uncertain data (to predict asset failure in energy networks)
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Probabilistic databases with MarkoViews
Proceedings of the VLDB Endowment
FDB: a query engine for factorised relational databases
Proceedings of the VLDB Endowment
Demonstration of the FDB query engine for factorised databases
Proceedings of the VLDB Endowment
The dichotomy of probabilistic inference for unions of conjunctive queries
Journal of the ACM (JACM)
Applying weighted queries on probabilistic databases
Proceedings of the 21st ACM international conference on Information and knowledge management
Evaluating indeterministic duplicate detection results
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
A top-k filter for logic-based similarity conditions on probabilistic databases
ADBIS'12 Proceedings of the 16th East European conference on Advances in Databases and Information Systems
Ontology-based access to probabilistic data with OWL QL
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
Indeterministic Handling of Uncertain Decisions in Deduplication
Journal of Data and Information Quality (JDIQ) - Special Issue on Entity Resolution
Proceedings of the 16th International Conference on Database Theory
ProQua: a system for evaluating logic-based scoring functions on uncertain relational data
Proceedings of the 16th International Conference on Extending Database Technology
Charting the tractability frontier of certain conjunctive query answering
Proceedings of the 32nd symposium on Principles of database systems
Efficient and scalable monitoring and summarization of large probabilistic data
Proceedings of the 2013 Sigmod/PODS Ph.D. symposium on PhD symposium
On scaling up sensitive data auditing
Proceedings of the VLDB Endowment
Real-time probabilistic data association over streams
Proceedings of the 7th ACM international conference on Distributed event-based systems
Colledge: a vision of collaborative knowledge networks
Proceedings of the 2nd International Workshop on Semantic Search over the Web
On the connections between relational and XML probabilistic data models
BNCOD'13 Proceedings of the 29th British National conference on Big Data
A temporal-probabilistic database model for information extraction
Proceedings of the VLDB Endowment
Aggregation and ordering in factorised databases
Proceedings of the VLDB Endowment
Query answering under probabilistic uncertainty in Datalog+ / - ontologies
Annals of Mathematics and Artificial Intelligence
Anytime approximation in probabilistic databases
The VLDB Journal — The International Journal on Very Large Data Bases
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Probabilistic databases are databases where the value of some attributes or the presence of some records are uncertain and known only with some probability. Applications in many areas such as information extraction, RFID and scientific data management, data cleaning, data integration, and financial risk assessment produce large volumes of uncertain data, which are best modeled and processed by a probabilistic database. This book presents the state of the art in representation formalisms and query processing techniques for probabilistic data. It starts by discussing the basic principles for representing large probabilistic databases, by decomposing them into tuple-independent tables, block-independent-disjoint tables, or U-databases. Then it discusses two classes of techniques for query evaluation on probabilistic databases. In extensional query evaluation, the entire probabilistic inference can be pushed into the database engine and, therefore, processed as effectively as the evaluation of standard SQL queries. The relational queries that can be evaluated this way are called safe queries. In intensional query evaluation, the probabilistic inference is performed over a propositional formula called lineage expression: every relational query can be evaluated this way, but the data complexity dramatically depends on the query being evaluated, and can be #P-hard. The book also discusses some advanced topics in probabilistic data management such as top-k query processing, sequential probabilistic databases, indexing and materialized views, and Monte Carlo databases. Table of Contents: Overview / Data and Query Model / The Query Evaluation Problem / Extensional Query Evaluation / Intensional Query Evaluation / Advanced Techniques