JOURNAL ARTICLE

An efficient semantic query optimization algorithm

Abstract

An efficient semantic query optimization algorithm is proposed, in which all possible transformations are tentatively applied to the query. Instead of physically modifying the query, the transformation process classifies the predicates into imperative, optional or redundant. At the end of the transformation process, all the imperative predicates are retained while the redundant predicates are eliminated. Optional predicates are retrained or discarded based on the estimated cost/benefit of retaining them. The issue of the grouping of semantic constraints to reduce the overhead of retrieving constraints and checking whether each constraint is relevant to the current query is also addressed. Based on the proposed algorithm, a prototype semantic query optimizer has been built and preliminary experiments show that the optimizer performs well for large databases.< >

Keywords:
Computer science Query optimization Overhead (engineering) Transformation (genetics) Query language Sargable Process (computing) Constraint (computer-aided design) Query expansion Algorithm Theoretical computer science Information retrieval Data mining Web search query Programming language Search engine Mathematics

Metrics

20
Cited By
1.14
FWCI (Field Weighted Citation Impact)
17
Refs
0.79
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Data Management and Algorithms
Physical Sciences →  Computer Science →  Signal Processing
Advanced Database Systems and Queries
Physical Sciences →  Computer Science →  Computer Networks and Communications
Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence

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