R* optimizer validation and performance evaluation for local queries
SIGMOD '86 Proceedings of the 1986 ACM SIGMOD international conference on Management of data
The EXODUS optimizer generator
SIGMOD '87 Proceedings of the 1987 ACM SIGMOD international conference on Management of data
Quantifying inductive bias: AI learning algorithms and Valiant's learning framework
Artificial Intelligence
Logic-based approach to semantic query optimization
ACM Transactions on Database Systems (TODS)
Learning in relational databases: an attribute-oriented approach
Computational Intelligence
A method for automatic rule derivation to support semantic query optimization
ACM Transactions on Database Systems (TODS)
An overview of query optimization in relational systems
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Analysis and performance of inverted data base structures
Communications of the ACM
Design and Implementation of a Semantic Query Optimizer
IEEE Transactions on Knowledge and Data Engineering
Automatic Knowledge Acquisition and Maintenance for Semantic Query Optimization
IEEE Transactions on Knowledge and Data Engineering
Logic-Based Query Optimization for Object Databases
IEEE Transactions on Knowledge and Data Engineering
Data-Driven Discovery of Quantitative Rules in Relational Databases
IEEE Transactions on Knowledge and Data Engineering
Implementation of Two Semantic Query Optimization Techniques in DB2 Universal Database
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Semantic Query Optimization for Bottom-Up Evaluation
ISMIS '96 Proceedings of the 9th International Symposium on Foundations of Intelligent Systems
A Statistical Approach to Rule Selection in Semantic Query Optimisation
ISMIS '99 Proceedings of the 11th International Symposium on Foundations of Intelligent Systems
Distributing the Derivation and Maintenance of Subset Descriptor Rules
ISAS-SCI '01 Proceedings of the World Multiconference on Systemics, Cybernetics and Informatics: Information Systems Development-Volume I - Volume I
Data Analysis for Query Processing
IDA '97 Proceedings of the Second International Symposium on Advances in Intelligent Data Analysis, Reasoning about Data
QUIST: a system for semantic query optimization in relational databases
VLDB '81 Proceedings of the seventh international conference on Very Large Data Bases - Volume 7
Storage and access in relational data bases
IBM Systems Journal
Automating model transformation by example using inductive logic programming
Proceedings of the 2007 ACM symposium on Applied computing
Model transformation by example
MoDELS'06 Proceedings of the 9th international conference on Model Driven Engineering Languages and Systems
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Semantic query optimisation is the process by which a user query is transformed into a set of alternative queries each of which returns the same answer as the original. The most efficient of these alternatives is then selected, for execution, using standard cost estimation techniques. The query transformation process is based on the use of semantic knowledge in the form of rules which are generated either during the query process itself or are constructed according to defined heuristics. Previous research has tended to focus on constructing rules applicable to single relations and does not take advantage of the additional semantic knowledge, inherent in most databases, associated with relational joins. Our paper seeks to address this weakness by showing how the rule derivation process may be extended to the generation of inter-relational rules using an approach based on inductive learning.