Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Indefinite and maybe information in relational databases
ACM Transactions on Database Systems (TODS)
A probabilistic relational model and algebra
ACM Transactions on Database Systems (TODS)
A probabilistic relational algebra for the integration of information retrieval and database systems
ACM Transactions on Information Systems (TOIS)
Query evaluation in probabilistic relational databases
Selected papers from the international workshop on Uncertainty in databases and deductive systems
ProbView: a flexible probabilistic database system
ACM Transactions on Database Systems (TODS)
Uncertainty in a nested relational database model
Data & Knowledge Engineering
Similarity-based ranking and query processing in multimedia databases
Data & Knowledge Engineering
A guided tour to approximate string matching
ACM Computing Surveys (CSUR)
Database System Implementation
Database System Implementation
The Management of Probabilistic Data
IEEE Transactions on Knowledge and Data Engineering
Integrity Constraints in the Information Source Tracking Method
IEEE Transactions on Knowledge and Data Engineering
Aggregation of Imprecise and Uncertain Information in Databases
IEEE Transactions on Knowledge and Data Engineering
Generalized Normal Forms for Probabilistic Relational Data
IEEE Transactions on Knowledge and Data Engineering
Learning Probabilistic Models of Relational Structure
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
The Theory of Probabilistic Databases
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Evaluating probabilistic queries over imprecise data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Approximate Selection Queries over Imprecise Data
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
MYSTIQ: a system for finding more answers by using probabilities
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Foundations of probabilistic answers to queries
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Approximate Data Collection in Sensor Networks using Probabilistic Models
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Avatar semantic search: a database approach to information retrieval
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Optimizing mpf queries: decision support and probabilistic inference
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
From complete to incomplete information and back
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
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
Efficient query evaluation on probabilistic databases
The VLDB Journal — The International Journal on Very Large Data Bases
Query language support for incomplete information in the MayBMS system
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Databases with uncertainty and lineage
The VLDB Journal — The International Journal on Very Large Data Bases
Combining intensional with extensional query evaluation in tuple independent probabilistic databases
Information Sciences: an International Journal
Top-k best probability queries and semantics ranking properties on probabilistic databases
Data & Knowledge Engineering
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Managing uncertain information using probabilistic databases has drawn much attention recently in many fields. Generating efficient safe plans is the key to evaluating queries whose data complexities are PTIME. In this paper, we propose a new approach generating efficient safe plans for queries. Our algorithm adopts effective preprocessing and multiway split techniques, thus the generating safe plans avoid unnecessary probabilistic cartesian-products and have the minimum number of probabilistic projections. Further, we extend existing transformation rules to allow the safe plans generated by the Safe-Plan algorithm [N. Dalvi, D. Suciu, Efficient query evaluation on probabilistic database, The VLDB Journal 16 (4) (2007) 523-544] and the proposed algorithm to be transformed by each other. Applying our approach through the TPC-H benchmark queries, the experiments show that the safe plans generated by our algorithm are more efficient than those generated by the Safe-Plan algorithm.