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Efficient Maintenance of Rule-derived Data Through Join Pattern Indexing by Arie Segev; J. Leon Zhao is a scholarly article available to read on EtoBox.

In intelligent database systems, knowledge-directed inference often derives large amounts of &@ and the efficiency of query processing in these systems depends upon how the derived data are maintained, This paper focuses on situations where data-deriving rules are conditional on joins of multiple data objects (or relations) and the derived data are materialized to reduce the overall query processing costs. Join indexing is needed for the efficient maintenance of such rule-derived daa but existing join indexing methods are not suitable for this purpose. We develop a family of join indexing techniques -join pattern indexing -based on a unique construct called join pattern relation. The performance of the proposed join pattern indexing techniques is evaluated to demonstrate their cost effectiveness.

Author

Arie Segev; J. Leon Zhao

Publisher

ACM Press

Published

1993

Language

EN