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Query evaluation and optimization in the semantic web

Published online by Cambridge University Press:  01 May 2008

EDNA RUCKHAUS ,
EDUARDO RUIZ  and
MARÍA-ESTHER VIDAL
EDNA RUCKHAUS
Affiliation:
Computer Science Department, Universidad Simón Bolívar (e-mail: [email protected], [email protected], [email protected])
EDUARDO RUIZ
Affiliation:
Computer Science Department, Universidad Simón Bolívar (e-mail: [email protected], [email protected], [email protected])
MARÍA-ESTHER VIDAL
Affiliation:
Computer Science Department, Universidad Simón Bolívar (e-mail: [email protected], [email protected], [email protected])
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Abstract

We address the problem of answering Web ontology queries efficiently. An ontology is formalized as a deductive ontology base (DOB), a deductive database that comprises the ontology's inference axioms and facts. A cost-based query optimization technique for DOB is presented. A hybrid cost model is proposed to estimate the cost and cardinality of basic and inferred facts. Cardinality and cost of inferred facts are estimated using an adaptive sampling technique, while techniques of traditional relational cost models are used for estimating the cost of basic facts and conjunctive ontology queries. Finally, we implement a dynamic-programming optimization algorithm to identify query evaluation plans that minimize the number of intermediate inferred facts. We modeled a subset of the Web ontology language Lite as a DOB and performed an experimental study to analyze the predictive capacity of our cost model and the benefits of the query optimization technique. Our study has been conducted over synthetic and real-world Web ontology language ontologies and shows that the techniques are accurate and improve query performance.

Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 8 , Issue 3 , May 2008 , pp. 393 - 409
Copyright
Copyright © Cambridge University Press 2008

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