Title :
Automatic knowledge acquisition and maintenance for semantic query optimization
Author :
Yu, Clement T. ; Sun, Wei
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Illinois Univ., Chicago, IL, USA
fDate :
9/1/1989 12:00:00 AM
Abstract :
The authors present an approach to acquiring knowledge from previously processed queries. By using newly acquired knowledge together with given semantic knowledge, it is possible to make the query processor and/or optimizer more intelligent so that future queries can b processed more efficiently. The acquired knowledge is in the form of constraints. While some constraints are to be enforced for all database states, others are known to be valid for the current state of the database. The former constraints are statistic integrity constraints, while the latter are called dynamic integrity constraints. Some situations in which certain dynamic semantic constraints can be automatically extracted are identified. This automatic tool for knowledge acquisition can also be used as an interactive tool for identifying potential static integrity constraints. The concept of minimal knowledge base is introduced, and a method to maintain the knowledge base is presented. An algorithm to compute the restriction (selection) closure, i.e. all deductible restrictions, from a given set of restrictions, join predicates (as given in a query), and constraints is given
Keywords :
database management systems; knowledge acquisition; knowledge based systems; automatic tool; constraints; database states; dynamic integrity constraints; interactive tool; join predicates; knowledge acquisition; maintenance; semantic query optimization; statistic integrity constraints; Constraint optimization; Database systems; Inference algorithms; Joining processes; Knowledge acquisition; Knowledge management; Query processing; Sun;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on