Optimization of query evaluation algorithms
ACM Transactions on Database Systems (TODS)
Developing a natural language interface to complex data
ACM Transactions on Database Systems (TODS)
SIGMOD '75 Proceedings of the 1975 ACM SIGMOD international conference on Management of data
Implementation of integrity constraints and views by query modification
SIGMOD '75 Proceedings of the 1975 ACM SIGMOD international conference on Management of data
A generalized access path model and its application to a relational data base system
SIGMOD '76 Proceedings of the 1976 ACM SIGMOD international conference on Management of data
Access path selection in a relational database management system
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
Improving Query Evaluation with Approximate Functional Dependency Based Decompositions
BNCOD 19 Proceedings of the 19th British National Conference on Databases: Advances in Databases
Dynamic Constraints Derivation and Maintenance in the Teradata RDBMS
DEXA '01 Proceedings of the 12th International Conference on Database and Expert Systems Applications
Query Optimization via Empty Joins
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
Constructing Inter-relational Rules for Semantic Query Optimisation
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
Semantic Query Optimization for ODMG-93 Databases
IDEAS '99 Proceedings of the 1999 International Symposium on Database Engineering & Applications
Minimizing response times in real time planning and search
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
On chase termination beyond stratification
Proceedings of the VLDB Endowment
Correlation maps: a compressed access method for exploiting soft functional dependencies
Proceedings of the VLDB Endowment
Using semantics for XPath query transformation
International Journal of Web and Grid Services
Semantic XPath query transformation: opportunities and performance
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
A utilization of schema constraints to transform predicates in XPath query
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part I
A fast transformation method to semantic query optimisation
IDEAS'97 Proceedings of the 1997 international conference on International database engineering and applications symposium
Efficient auditing for complex SQL queries
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Alternative query generation for XML keyword search and its optimization
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part I
Semantic knowledge integration to support inductive query optimization
DaWaK'07 Proceedings of the 9th international conference on Data Warehousing and Knowledge Discovery
Semantic query optimization in the presence of types
Journal of Computer and System Sciences
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Semanfic query ophizotion is an approach to query optimization that uses knowledge of the semantics of the data to transform a query into another query that has the same answer but can be processed more efficiently. However, the indiscriminate application of semantic transformations can itself be excessively costly when there are many semantic rules upon which transformations can be based. This paper describes a semantic query optimization system called QUIST (Query lmprovement through Semantic Transformation). QUIST demonstrates significant cost reductions for a class of relational database queries. At the same time, QUIST uses knowledge about relational database structures and processing methods to insure that semantic transformations are applied selectively. This knowledge reflects cost models and optimization techniques developed in recent query optimization research. To integrate semantic, structure, and processing knowledge, QUIST analyzes a query at several levels of detail, along the lines of the plan-generate-test paradigm of artificial intelligence systems.